๐๐ฎ๐๐ฎ ๐ง๐ฎ๐น๐ธ ๐๐ถ๐๐ต ๐๐ฎ๐ฟ๐ฎ๐ฎ & ๐ง๐ถ๐บ
Tim and Barra swap origin stories, debate Tableau versus Power BI, and agree the real skill isn't the tool, it's understanding the business.
- Learning a business domain means living the process, not just reading documentation or staring at data models
- Tableau and Power BI aren't true like-for-like competitors, most comparisons are really just Tableau Desktop versus Power BI Desktop
- Tool choice is usually driven by company infrastructure and licensing, not individual preference, so don't over-invest in tool wars
- Being a flexible bridge between business problems and data solutions matters more than chasing a specific job title
- Deep expertise compounds slowly over years, not weeks, so consistent daily learning beats cramming a certification
- Welcome and how Barra got inspired by Tim0:59
- Tim's background and path into analytics consulting14:22
- Barra's accidental path into data engineering19:18
- Data engineer vs analyst: blurred role boundaries21:57
- How Tim approaches learning a new client's domain26:16
- Living the business process to gain domain knowledge34:04
- Why the channel is called Tableau Tim40:27
- Tableau vs Power BI: philosophy and ecosystem differences44:27
- Choosing tools based on licensing, scale and use case48:36
- Career advice: why skills compound over time53:22
0:08So let's see
0:13I think we are live now.
0:15Awesome.
0:16Yeah, Seth's live 17 seconds.
0:19Nice, nice.
0:20Glad to see this.
0:22I will just grab those stuff here.
0:25It is live.
0:26So yeah.
0:27We are live then.
0:29Hey mates.
0:30Finally.
0:32Finally.
0:33Exactly.
0:33So I think uh people are gonna start joining slowly uh our live stream.
0:38Yeah we have already from my side, I think twenty.
0:42Let me just test whether the voice is there.
0:45Yeah, it looks nice.
0:47Good.
0:48Yes.
0:49And at your site as well, it is live, right?
0:51Yeah, yeah.
0:52Yeah.
0:52It's live on the channel.
0:53If you're live, I'm live as well.
0:55This looks good.
0:56Nice.
0:56Looks good.
0:57Okay.
0:58So everyone, hey.
1:01I would say welcome to our live session.
1:06Finally, finally.
1:07Um, today is with me Tim.
1:10Uh and we're gonna take talk about like a few different topics.
1:14It's gonna be open conversation to be honest.
1:16We didn't prepare anything, so there will be no let's say agenda about the video, but we're gonna talk about
1:22Our careers, uh, Tim comes from uh analytics worlds, I come from data engineering worlds, we both work
1:31um in different companies and as well we have YouTube channels.
1:35That's why we're gonna talk about as well about content creation, about our experience.
1:39So we're gonna have an open talk about it
1:41And um yeah, you can drop your questions in the chats and I will pick from time to time some questions.
1:48And at the end, we're gonna have completely just QA.
1:51You can ask me and ask them anything you want.
1:54So hate him.
1:55How are you mates?
1:57I'm good.
1:58We've talked for so long.
1:59It's sort of weird introducing me.
2:01But yeah, it's a pleasure to be here.
2:03Love, love, love meeting your audience and yeah.
2:05I'm glad we've finally done this.
2:07Thank you for getting me out of my box.
2:09Yeah, you are.
2:10You are very welcome.
2:11Yeah, I was waiting for this like a long time ago.
2:14I think we speak about it
2:15Last month uh last year, last we're gonna go live stream together and I was always excited about it because I never went live, but now a dream comes true and I am here with uh Tim Tableau.
2:29Um
2:30There is a story behind um me and Tim.
2:35To be honest, it is it is not just like uh okay we are um
2:39both in the data world and we have YouTube channel, there is like some inspiration story behind it.
2:44And maybe I'm gonna tell some back, let's say behind the scenes little bit, because maybe some of you don't know Tim or don't know how I actually started my YouTube channel.
2:53Now the thing is three, four years ago I was yeah, checking YouTube.
2:58Yeah.
2:59And I was very involved in one topic, like what is better, Tableau or Power PI?
3:04Because I have to decide for one of the projects about it
3:07And I was like making some slides and stuff at the work.
3:10I was really busy about it.
3:12And then in YouTube I saw a video from Tim.
3:17Uh it was about what is Tableau.
3:19I worked with before with Tableau, but it was only like 10 minutes from Tim.
3:24And
3:25I was engaged in the whole video, like the whole 10 minutes.
3:28I know what is Tableau.
3:30I know how Tableau works and how we use it.
3:32I already used it in many projects.
3:34But it was the storytelling of Tim, it was amazing.
3:38And I was like, oh my God, exactly this what I love.
3:42And I was think about why not start a YouTube channel?
3:46Why not to talk about those stuff like Tim?
3:49Why don't I go like and start comparing Tableau and Power BI, not only for the work, I just show it for the world, you know?
3:56Yeah.
3:56So I got inspired from Tim, from his one video.
3:59What is Tableau?
4:00You can check it.
4:01Uh you can check his channel.
4:02I think it his has like more than one million views.
4:05It was amazing video.
4:06And I remember at the start I saw something from him that he said in the video, you know what, I'm not turning any ads on this video.
4:13It's gonna be like free.
4:15So he's not getting like anything in return about this video.
4:19And I was really inspired from Tim.
4:21So the idea came inside my head and I started thinking about it all the time.
4:25I'm gonna start a channel.
4:26I'm gonna start channel.
4:27Then I started one and the first topic, the first video I was talking about Tableau.
4:33Now uh I made around, let's say, yeah, 40 videos about Double.
4:39And I was not sketching yet.
4:41It was only like PowerPoint presentations and just like click around.
4:45And then I had like around 300 subscribers.
4:48Yeah.
4:49And each video, like 10 views, 20 views.
4:52Yeah.
4:53Then someone wrote me in LinkedIn and told me, hey Bara, you are doing amazing work.
4:58And it was like
5:00Oh my god, is it the same guy that got me inspired?
5:04So I was like really uh I yeah, really happy that I reached Tableau somehow, Tim somehow.
5:12And uh I I was really honored, you know.
5:14It's like big achievements.
5:16So that Tim is talking to me and he was very nice about it.
5:19He told me
5:20You are doing well.
5:21You know, this data content creation is something really, let's say, hard at the start.
5:25You are alone.
5:26Yeah.
5:27And um yeah, keep doing what you're doing.
5:29I like your thumbnails.
5:31And then after a few days, I saw that Tim is speaking about my channel in one of his videos.
5:36And it was crazy because I was never like I thought I'm just making the videos for my friends and stuff.
5:43Like it was
5:44I didn't take it seriously at all, but he was like a mentor from ETEM.
5:49And I start checking as well behind the scenes.
5:51He has a lot of videos or let's say a blog article and as well.
5:55He was showing he how he was catching, yeah, behind the scenes.
5:59And I got totally inspired.
6:00So I bought an iBot.
6:02I hadn't had one.
6:04I got the brokerate
6:06Yes.
6:07And he explained step by step he the process, how he was doing it.
6:10And I started sketching the first concept in Tableau.
6:13It was about the filters in Tableau and something like that.
6:16And people loved it.
6:17People loved it.
6:18So I can say
6:20Tim for me is big inspiration.
6:23He was, let's say, the reason why I started this channel, why I started using this style by sketching.
6:28I use a lot of PowerPoint at work, you know, to explain things for managers.
6:33But as I was um yeah checking the sketching, I was think thinking, this is exactly what I need.
6:39This is exactly what uh the correct way to explain things.
6:42So
6:43Tim, you were really crazy inspiration for me and thank you for that.
6:49Absolut absolute honor.
6:50I uh
6:52First of all, thank you.
6:53Thank you for the context.
6:54I have to say, when I when I found your channel for the first time, what I understood already, because I'd had a YouTube channel from a year, is that when you start
7:05YouTube does a very bad job of showing your content to the right people.
7:08It's still learning.
7:10And I personally felt that you you had already achieved what I'd achieved in the first year and were doing it really, really well.
7:18And you just started.
7:19So I sent you that message because I knew where I was.
7:22I nearly gave up multiple times and I was like, no, you've got to keep going.
7:26Like just please trust me on this one.
7:28You gotta keep going.
7:30And then you took this um sketch, and I I remember saying the reason I made that blog post was because I genuinely knew that if other people tried this approach.
7:41Um, it would work, but I also f kept being asked myself, how do you do this?
7:46And I thought, well, there's a lot of work involved with this.
7:49But maybe if someone's really passionate about this, if at least you know one or two people do this, then some other great content will be out there.
7:57And I have to say you're the only person that read that blog post.
8:01Did did the did the steps exactly as I described and you nailed it and I was like, oh my word.
8:07It it like it worked.
8:09And then I was like, I just watched you turn it into your own style and everything.
8:13I was just like, nah, this is another level now.
8:16Like you've you understood the assignment and you absolutely knocked it out of the park.
8:19So I I am forever grateful that you took that step to just, you know.
8:24Follow that inspiration because that's why I made that blog and you you nailed it.
8:28So I I'm happy.
8:29I'm really happy that that idea sort of went and it's not original.
8:32I didn't do sketches for the first time.
8:34Other people have done them, but I think I
8:36I showed that it could be possible in the data world and other people are doing it.
8:39And I think you see sketches a bit more as a style, uh definitely in the data space.
8:43But yeah, making it into video is hard work and yeah, you absolutely nailed it.
8:49Thank you.
8:49Thank you.
8:49Yeah.
8:50I am happy that you are happy of the the result.
8:54And this is exactly like the world of content creation.
8:57You inspire others.
8:58Like sometimes I like not sometimes.
9:00Many times I get like some nice messages to tell me, you know what?
9:03Because of you, I started my data engineer, let's say, journey and now I got hired and stuff.
9:09So this is one of the most, let's say, beautiful moments at content creation that you see the effect of your work.
9:16Like you see, one person like me did believe on your article, did believe that
9:22This is the right way and look, I'm helping now as well many people in my channel and making courses, breaking those complex concepts like into sketches.
9:32So this this is something that I really enjoy by making contents.
9:36To inspire others.
9:37This is correct.
9:38Like I was afraid a little bit that you think you know I'm copying you.
9:42Nah, but I was trying I was trying to add as well my touch.
9:47Because, you know, it is uh yeah.
9:50I try to learn from you how you sketch, how you do the editing, but I tried not to copy you one to one because
9:57I'm not trying to turn to to be like you because then we will just like having care of different people.
10:03So we have to
10:04Get inspired really from the others and add add for it our own touch.
10:10And this is how the world works, really.
10:12If you look to the car industry, you see those big companies, you see the models of the cars, they are always like you see
10:18Like I saw this model before from other combat.
10:21They get inspired from each other's.
10:23Yeah.
10:24There is there will be really um
10:26Like only few memo moments where you bring some something from the scratch from your own ideas.
10:32So it's all always like this.
10:33You get inspired, you add your own flavor, and then you move on, right?
10:37Yeah.
10:38Yeah.
10:38And and you know you've you've
10:41You've done a lot of um very unique things with the format and I think you've you've shown ideas that I didn't even think I used to think that if I was gonna do these sketches I would need to have like
10:54some fun animations and you know some fun creative things that weren't data in in in the in the sketches.
11:01But you've taken this, I've seen some of your Databricks content and you're describing what I would say is very
11:06dry, difficult content in the Databricks ecosystem in a very engaging way.
11:12And the way the diagrams bring it to life, I think makes it so much more interesting for everyone who's
11:17learning a very difficult topic and it make it it it it widens the opportunity because people who have different learning styles, different ways of learning
11:26have multiple ways they can engage with you.
11:27They can listen, they can watch, they can go read the textbook and then they come to your channel and they get that visual additional step that just gets them over that line and suddenly now they're passionate.
11:38And so you've enabled, I'm sure, many, many thousands of people, um, you know, to to to learn just because you've taken that format to another level and
11:46That is art.
11:47That's how art works.
11:48Art is about inspiration, building on other people's work, taking it to the next level, adding your own style.
11:54And I think being a creator is very much that.
11:56If you don't have any sort of artistic um, you know, bone in you, then you would just copy someone.
12:03And I think YouTube is full of copycats, right?
12:05You have lots of stuff that is
12:06very much, oh, I've seen that work over there.
12:08Let me do the same.
12:09Let it let's get, you know, a hundred thousand views.
12:12Not many people take something and innovate in it.
12:16And I'm I again I'll keep saying this forever.
12:18You never copied me.
12:19It was
12:19You you made it something else.
12:21I've said this to you like personally.
12:22I've said like you've you just you just you you took the playbook, you just totally knocked it out of the park.
12:28I'm always impressed.
12:29And it's hard, like I can never describe to people
12:31How hard it is to do this thing.
12:33Like in Procreate, get it into like uh DaVinci Resolve or Premier Pro, then animate.
12:38Like it's it's so many steps.
12:40And yes, you can use tools to do this, but
12:44If you understood the the the depth of work required to make it happen, you would have ten times more respect for what Barra is doing because
12:52It takes time and real time and effort and skill.
12:56And you've improved as well.
12:57I've seen you like kind of grow and enhance it as well
13:00It's amazing.
13:00It's so good.
13:02Yeah, yeah.
13:06But over the time they
13:08The persons I'm adding, the I add for them some hair, some glasses, some colors.
13:15Now I have like three three templates that are always follow.
13:19A guy with a glass with long hair and another girl.
13:22So I try to make it, you know, universal.
13:25Yeah.
13:25But it it is fun.
13:26It takes time, maybe for people that are not uh following us.
13:30Um IMIC and TEM make sketches using procreates, so we draw with uh hand draws with our hands
13:37The sketches, it's gonna get animated with a procreate, and then we use DaVinci Resolve in order to do the last touch if you want to zoom in and maybe remove retakes and stuff like that.
13:48So it is really
13:50A hard manual process.
13:51I don't believe AI so far can help me with this.
13:54It can give me some ideas about it, but still, this is totally hand uh draws and uh yeah, it takes a lot of time, takes a lot of time.
14:02Sometimes on I spend like like really two hours just making one simple sketch because it is animated.
14:09But now you know what?
14:10Um I would like to take a step back and maybe you maybe some people here don't know you yet
14:16Tim, could you give us like some little intro?
14:19Who is Tim and what you are doing now?
14:21What are your plans?
14:23Yeah.
14:24Um
14:25So I'm an analytics consultant.
14:27Um I work for a company based in America called Aimpoint Digital.
14:31I've been an analytics consultant for 12 years and um a large part of my job, I'm a principal, so a large part of my job is helping
14:39deliver, let's say reasonably large projects across various companies.
14:43So typically engage with a client for anywhere between three months to just over a year and typically working in the team.
14:52Um I I got here because I started out at a company called the Information Lab.
14:57Um that's when I started with Tableau.
15:00Tableau was the was was my first thing in data.
15:03I came
15:03from a marketing background.
15:04So I was already working with social media data about 12 years ago, but it wasn't great.
15:09And so um uh someone called Craig Bloodworth who worked in information lab.
15:13He was a Tableau visionary at the time, said, Hey, would you like to come and work with us?
15:18We work with data and we can teach you this thing called Tableau.
15:21So I thought, well, why not?
15:22This is a great opportunity.
15:23So I went
15:24And I started consulting and yeah, I've never looked back.
15:28I I worked with that company for eight years in total.
15:30I worked briefly at Accenture
15:32And now I'm working at Aimpoint Digital.
15:34I've been I've been here for two and a half years.
15:36And so just really enjoying the opportunity to um work on real projects.
15:40And it's it's a balance I like to keep with content creation because
15:44I I learned so much on the job that I've always felt that if I stopped working, I would I would lose that ability to learn new things because a chat clients are challenging me to learn.
15:55And so that's why I've I've sort of held on to this principle of, yes, I make content, but my primary thing is my career and um that's what I love doing
16:03So yeah.
16:04Nice, nice.
16:05Yeah, I've been I've been there, you know.
16:08Only three months is left my work.
16:10But um
16:11How did you decide to do analytics?
16:13Like there is a lot of things in the tech industry, you know, to be software engineer, to be yeah um maybe data engineer, data scientist.
16:21So l
16:21Why exactly analytics and what like how how was the start?
16:24Is it like something you understood and decided to be analytic or was it like coincidence?
16:29It's a complete coincidence.
16:31And if I look back at my career, some of the best decisions I've made have been
16:38not say coincidence but accidental.
16:40Right.
16:40And what what I'll say is the common thing between all of them is that I've I decided to give it a go.
16:45Right.
16:46There wasn't anything telling me no, this is a bad idea.
16:48So I gave it a go.
16:49So when I joined the information lab
16:51to get into um uh data in my head i was getting into consulting and tabloid i wasn't really entering analytics
17:00And as I started doing the work, I started learning Tableau, I started consulting Tableau, I slowly learned more and more about analytics, but I did it through the lens of Tableau.
17:09Then I think two years in, I realized
17:12that the the world of analytics was a lot broader than just one tool.
17:15So I then decided to start exploring other things, other technologies.
17:19Altrix is another one that I've been using for almost as long.
17:23And so I started doing what we would probably call data engineering and data pipeline work today, but doing it all inside of a tool called Outrix.
17:31So basically making the Tableau visualizations come to life by modeling the data in Altrix.
17:36Um and then I just really enjoyed it.
17:39Um it's like a a visual data prep tool, if that makes sense.
17:43Okay.
17:46Strictly speaking, I wouldn't quite frame it as an ETL tool in the modern day context.
17:50It's it's like you could do the kind of things you do in DBT, but you do it through a visual work, through it has a um, you know, a cloud capability.
17:58It's not um, I would say a um it's not a tool that I think a lot of people will have come across.
18:04It's a very, let's say, niche tool, works in a lot of uh enterprise context because
18:09It allows business users to build their own data pipelines very quickly instead of doing it in Excel or having to learn Python.
18:16And so that's why it's it's very popular.
18:18amongst lots of clients.
18:19So yeah, I was an all tricks and tableau person for nearly a decade.
18:23And um I learned a lot about working with data, spatial analytics, you know, statistical analysis, predictive modeling.
18:30And I just loved that every single time I thought I understood the topic, it threw me another challenge that just took me to another level.
18:37And I just felt like, man, like, why would I leave a job where every single year
18:42I keep getting challenged, the technology gets better.
18:45And, you know, halfway through that, I started to realize, hey, it turns out working in tech and data is actually a pretty big deal.
18:52So I happen to just
18:53coincidentally land in a really fortunate position.
18:56So yeah, I've stayed in that uh in in that path and I've always said to people, hey, the only reason I'd leave uh analytics or
19:04data in general is if it stops challenging me and I stop sort of having that passion to want to learn more.
19:09And yeah, it's never done that.
19:11So here I still am.
19:13It will never be boring, yeah, working in that.
19:16Exactly, exactly.
19:17Yeah.
19:18Like it is it's always interesting to hear the starts because the starts are always very random.
19:24I can tell you maybe some
19:25Of you don't know how I did start.
19:27I was a student, Tim, doing my bachelor's degree.
19:32And I wanted to work in a company just to go inside and to try, you know, as a student.
19:39uh we call it here um yeah uh helping um force in Germany.
19:45So I um yeah I went to a company and I don't know b
19:48uh PHP and I know like web development, I know data science stuff from the yeah first two years.
19:56Like I can do some predictions and stuff.
19:59And yeah, and uh there was like a big company in the city and they said yeah, we need some students to work with us.
20:05And they were they had like an open position to develop things in Java and PHP.
20:10So I thought, okay, this is perfect for me.
20:12I went there
20:13And then in the interview, they told me, you know what, we are really sorry, we found someone already.
20:18But we have another open position as a data warehouse developer, ETL developer.
20:25And I didn't understand at all what he's talking about.
20:28Like what is a data warehouse?
20:29What is an ETL?
20:30But I was disparate for a job, you know?
20:33So I saw, you know what?
20:35It's no problem.
20:36I'm gonna do that.
20:37I will do that.
20:38As long as it is it is relevant to the tick.
20:41Yeah, I said okay, I'm gonna do that.
20:44And I got in love building ETLs and building data warehouses, building stuff in databases.
20:50And then that that shapes
20:53the whole journey of my life.
20:55Exactly.
20:55I am big.
20:56I became because of this a data engineer.
20:59And I went and took master degree as well in data engineering.
21:03Wow and
21:04Seventeen years just doing that engineering.
21:07It's because of this one like uh event that happens in my life
21:12Yeah.
21:12I was going in direction of Java developer, but the position is already taken and they moved me to that engineer.
21:19Another path.
21:20Yeah.
21:20And this shaped the whole life, you know.
21:22Not something that I really
21:25Uh decided, you know, it's like something um yeah, totally randomly that happens.
21:30And if it's I'm really happy about it, happy about it because
21:34At at that time, it was really easy to find any job because uh um fewer people did have really data engineering skills.
21:42And I think until now, it is not that popular, you know, to be data engineer.
21:45So that's why I'm really happy that I picked this one.
21:48Or let's say uh this happened to me and which is that was that was that was awesome.
21:55And I stick to it until now.
21:57I'm just teaching about things about data engineering, but of course
22:01Um in our work, I don't know about you, but in many projects that I have done, I was as well doing analytical things and data science things because
22:11In many companies, they still don't have this clear separation between, you know what, you are a data engineer, you are data analytics scientists.
22:18I'm just a data guy for them, you know?
22:21Yeah, especially if you are working directly with a business, they don't really give a crap about what title you have.
22:27They need the data out from those systems.
22:31They want some some analytics at the end.
22:33So I cannot just go and say, you know what?
22:36My part ends as I extract the data and prepared because I'm that engineer.
22:40Well, I done a lot of projects where I do things end-to-end.
22:43So I think maybe you had some similar things, right?
22:46It's that absolutely.
22:48Absolutely.
22:49It's w it's a weird um
22:53thing like we we sat here saying hey we chose this sort of we kind of accidentally chose this path but the roles in data and analytics especially within organizations have constantly been evolving I think every two years
23:06There is a slightly different way that you could think of, you know, a BI developer, a data analyst, a analytics engineer, a data engineer, or you know, where like so many terms.
23:17And what they try and do is they try and define a group of work, but in reality, especially if you work in a small organization
23:25What people really want are bridges.
23:28They're looking for people that can get from this concept that they have in their head that they need to achieve with data.
23:35to the solution and whoever can step into that role, whoever can fill that bridge and get them across, they'll just work with them.
23:42So I've always said to people like think about yourself.
23:44as a bridge to the business.
23:46The business has a bunch of problems and challenges.
23:49Um they also have the data, I hope, in in a good way, maybe not in a great way always.
23:55And
23:55If you can get them to the solutions, the answers, and actually help them genuinely do the thing they're trying to understand, then it doesn't matter what you're called.
24:04You know what I mean?
24:09That's partly why I like consulting because um uh my clients don't see me as a data analyst.
24:15They don't see me as a data engineer, they just see me as Tim.
24:18He's a consultant, he's here to help us solve this big problem.
24:21And it just allows me to freely go between topics without needing to tell them, hey, I'm a data engineer, I can do that, right?
24:28And we have teams at my company that do data engineering specifically.
24:32But it gives me the autonomy to bring them in.
24:34It brings me the autonomy to say, hey, you should look at our data science uh guys that, you know, that think they can do some awesome stuff there for you.
24:41Um and that freedom I think allows you to explore topics in way more depth.
24:45And yeah, I think that's if you can get that opportunity to work in a in a role that
24:50doesn't have those boundaries, then that's a really good way to grow your career very quickly.
24:54I think it can really help you be exposed to lots of challenges very quickly.
24:58Yes, I I th I think the same.
25:01It is like um in only fewer projects we were had those pr like predefined roles.
25:08In most of cases we do everything actually in the data words.
25:11Now I would like to ask you something.
25:12You said you worked um or you are still working as consulting.
25:16Yeah.
25:17Now I find it this is something really challenging.
25:20I was consultant for around two years only, but I always switch back to
25:24to the product team, to the business.
25:26I see.
25:27Like uh working to the client directly there.
25:29Um I found it challenging to be a consulting because you know what once you enter new projects
25:35It is not about like to build a dashboard or a report.
25:38It's about to understand the business, the processes.
25:40And we had a lot of struggles.
25:43In different companies, like I always we always start new projects, we as well hire some consulting company to work with us, but they take a lot of time to understand the business to get something out of their work because
25:57They have to understand like how Mercedes-Penz work, for example, and how the processes, they have a lot of questions, and it's this very slow phase.
26:05And sometimes, really, a whole year could
26:08Go through and still some people still don't get it, don't get how to do analysis.
26:14So, how how you do that?
26:15Because you have now 12 years of consulting.
26:18And I'm sure you you went through different projects.
26:20So how yeah do you kick off any projects as analyst?
26:25It is funny.
26:26Um
26:27It the what I will say is um okay, let me first set the scene.
26:31I've I've consulting for um over 70 clients over twelve years.
26:36Um, I've mostly worked in three sectors, so insurance, finance, and let's say consumer goods.
26:43Those are the three high-level categories.
26:45Um, what you tend to find in consulting is once you've worked in certain sectors for a period of time, um, you've seen enough of what I would say um working patterns of different types of organizations.
26:57So
26:57Whenever I land on a project, the first thing I try and do is I try and understand what's the culture, what's the sort of working style of this company?
27:04How do they like to get things done?
27:05Are they super structured and they like everything documented or are they very like, you know, goal-oriented and they just want to get things done?
27:12The second thing is what's the business domain?
27:15So
27:15Um, what problem are you actually trying to solve?
27:17So if I go to insurance, I might be looking at let's say claims analysis, analyzing claims.
27:22And so I I try and do as much research as I can to understand that topic from the client's perspective.
27:29So I'm never really arriving with like zero context of what the business activity is.
27:33And it helps that I've done some work in those industries.
27:36So I have that three working with the data.
27:38But then the final thing is actually um distilling the problem.
27:42A lot of data problems are just the same problem in a different context.
27:47And so um I think I've been fortunate enough to work at companies where
27:51We just cut to the chase.
27:53We don't sort of come in with like 50 people to do like a very small thing.
27:57Typically I work solo, so I don't come in with like 10 other people.
28:01Yeah.
28:01Okay.
28:02Normally I'm an I'm on my own with a client.
28:04So this is I've worked for very small consultancies that don't come in with you know twenty, thirty, fifty people.
28:09Accenture was the only exception actually.
28:11First first time I went to Accenture and turned up to a Tableau uh engagement and there was like seven of us.
28:17I was like
28:17What is everyone doing here?
28:18I could do this all myself.
28:22Okay.
28:23But then I learned I learned very quickly, like they were there to be chargeable and I was there to teach them how to do the stuff.
28:29And I was like, okay, I get it now.
28:32I this is how this is how this works.
28:34But in in most other companies, it's just been me, one or two other people.
28:39We go in very small team.
28:40We've got six months, got a very specific thing.
28:43We almost become employees of that organization.
28:46And that's how we achieve outcomes.
28:49The company I work for at the moment, we have this very outcome focused promise that look, if we don't do what we pledge to do,
28:56um you get your money back.
28:57So everyone is very good and capable at their job.
29:00We work very hard with our clients to be able to make sure that we truly understand the problem that needs to be solved.
29:07And we also make sure the client understands the problem because sometimes they'll say to you, here's a problem, and we look at it and you go, actually, that's that's not the problem.
29:15There's this other problem.
29:16Are you are you really sure that you want to solve that problem?
29:19Shouldn't we solve the whole problem?
29:21And that opens up opportunities for us to really help them in big ways.
29:25And so a lot of our clients, especially the larger ones, bring us on board to do that.
29:29But even then, it's like two or three people.
29:31It's not like
29:32you know, 15 consultants going to one place.
29:34So yeah.
29:35It may be a different style of consulting.
29:38That's great.
29:39Um
29:40Maybe one thing you said you sit like it's what is really important for me to understand how you search for the domain.
29:47I know that now you have all the knowledge about this the sector and you know how things work in the finance and stuff.
29:52Yes, your first day as you wanted to learn the no the domain.
29:56Yes.
29:57How did you approach that?
29:58It's like did you read some documents or did you like dig into the data?
30:02Like what I've done from my side, I just like opened the database, I opened the model.
30:07Reading document and start playing with the data.
30:10Yeah.
30:10Each of us has different approach.
30:12So how what is like from your perspective the fastest way to learn the domain?
30:16Because I think this is the hardest part.
30:18Like building dashboards in Tableau or Power BI is the easiest part.
30:22Like how do you learn the domain?
30:24This is I think the
30:28The first detail is understanding which level of the business you're going in.
30:33And the way I describe this to sort of junior colleagues is you look at the company in a horizontal
30:41sort of segment or you look at it in a vertical segment.
30:44If I explain what those two are.
30:46So if I look at a problem in a horizontal segment, let's say I'm going into an insurance company.
30:51The horizontal segment is we're analyzing claims.
30:55Okay.
30:55And we're analyzing claims and claims will go through the actuary, the insurance teams, they will go through the telephone team.
31:03Everyone in the company touches that data.
31:06So if you understand how that problem works, looking horizontally as a section through the company, then you understand the way the business works.
31:14Then the other perspective is you want to understand the verticals.
31:17When you understand, let's say, insurance claims from a vertical perspective, you take one part of those teams.
31:23So you'll take maybe the telephone company.
31:25And you just you just look at the people who sit on the telephone processing insurance claims and you ask yourself, what is it they do to process an insurance claim?
31:33And you just go really deep into that analysis.
31:35And so
31:36You take a horizontal cup, then you take all the verticals within that, and you go into each vertical and you just build a picture.
31:42It's not hard because often you're a customer of some of these services.
31:46Maybe
31:47you know, you've maybe done an insurance claim.
31:49If you haven't, it's very easy to go online to website and try and get an insurance policy.
31:53You don't have to buy it, but you can go through the process.
31:55You can call them up and ask them questions.
31:57And so I've done this.
31:59Um when I worked for a supermarket, I was analysing price promotions.
32:03So um I actually asked the client, can I just go spend half a day in the supermarket just looking at all these promotions
32:09So I had all the data.
32:12I had all the data and I went to I went to Tesco here in the UK and I was taking pictures of all the promotions and I was like, so those are the aisles, these are the data.
32:20And then when we sat down to talk about the problems
32:23I had this like perfect mental model of exactly the problem.
32:27They were talking about displays.
32:29I knew what those looked like.
32:30I that, you know, they were talking about certain types of promotions.
32:33And I think I just got really deep into the topic.
32:36And if you just spend
32:38And it's hard because a lot of businesses don't give you this flexibility to say, hey, um, yeah, go spend a day in a supermarket and understand how pricing works.
32:46It's very undetailed.
32:47You need some context.
32:48But I think if you can just take those opportunities to work alongside, you know, your client, work alongside your colleague, and just understand those silly questions.
32:56Don't just look at the data.
32:57Really try and understand
32:59There is some human activity generating this data.
33:03There always is.
33:04Someone is literally doing something manually or physically and the data is being captured.
33:09You know, when you buy a chocolate bar, someone scans it at a till.
33:13for it to turn up as a record in your database.
33:16When someone buys a car, someone went into a dealership and signed a contract, right?
33:20And so if you can just think that through
33:23You start to understand everything that you need to understand to solve the data problem.
33:28Because you can ask, well, when they signed the contract, how did you capture their name?
33:31Did you
33:32get them to write it or was it typed in?
33:34If they wrote it, well the data quality is going to be awful.
33:36If they typed it, great.
33:37Did the database have all the, you know, name fills in the right place?
33:42Does it does it account for different character sets?
33:44You know, all these little things that you just don't think about and suddenly become huge problems that we then have to solve as engineers or analytics professionals.
33:52And so
33:53I know I've rambled for a bit, but that's all get super deep, super deep in the topic, then try and solve the problem um after that.
34:03I think this is exactly the key to succeed, yeah, and l learning the domain.
34:08This is something very important to live the business process, not to read about it.
34:13Like um we had an issue, uh one of yeah, one of the projects where it is really hard to understand how the machines are working.
34:21So it was like a place where it is like um yeah producing some machines in the car and we never understood it in the team.
34:30So what we have done, we spent three days
34:33Near to the factory, in the factory, looking how the process, how the machines are like connecting things and moving things, and why there is an issue there, where is the bottleneck?
34:43We saw it in our eyes, you know.
34:45And what we have done, we went to Tableau and we draw the factory machines really as a background image, and we just made some dots on the screen, and it was one of the most successful, let's say, overview that we had.
34:57And that's because we lived the process and we all understood it once we spent like only three days.
35:04It was not like I don't have to spend the whole month there.
35:06Only three days.
35:08We just ask people around as you saw as you said, yeah, silly questions around, and we got it.
35:13So I believe as an analyst, you have really to live the process.
35:17You have to you have to do you have to do it.
35:19I worked as well one of the energy companies.
35:23And I it was really complex here in Germany how the processes and how the documentations and how we like order new contract and stuff.
35:31I didn't get it because I was new in Germany.
35:33So what I have done
35:34I picked one of the customers and I went through the history and stood okay.
35:39At this point the order is done, then he canceled, then got the invoices and stuff.
35:45So I lived
35:46his like let's say story through the data as well.
35:49So this is as well something that's you have to live the process to understand it and then you're gonna gain the domain knowledge because
35:57Once you have it, then you are key player in this company because you can master both of the domain, the business, and as well the technology.
36:05Yeah.
36:05Because there will be a lot of people that can only do technology.
36:09They are very good at Power PI or Tableau, but zero understanding of the processes.
36:14Correct.
36:15So I think as an analyst and I think as well not only analysts, engineers as well, they have to start doing this because
36:22I had like in my last projects, 20 people working in my in in uh in it and we have a lot of engineers.
36:28There was only one girl that did understood the processes.
36:31And she was the only one that's building the data model because we have to build the model at the end, you know, the star schema, the the uh the models that we can provide for the users, and without having the business knowledge as an engineer as well
36:44Yeah.
36:45It is it is a struggle because um I had like yeah let's say a lot of a lot of developers they can do amazing things like connecting Kafka, connecting APIs and stuff, but they all stop at the same point
36:58Like once the data are inside, they cannot do anything with it because they have no idea how to do that.
37:03And this uh this uh woman was really a key player in the project.
37:07She was engineer and at the same time she know the process
37:10It was only she was curious about the data and she wanted to understand the the process, the business and the company and she was very successful now.
37:19Like I can say in the projects we were fighting where she where she stays, you know, because she was really precious for any project.
37:27So it is
37:28If especially at this time now, Tem, it is really let's say scary times, yeah, that you're gonna get replaced maybe with the AI and stuff.
37:36So you have to make sure to know what the company really needs and to master this, not the tools.
37:42From my point of view, the tools can like disappear or change over the time.
37:45Yeah.
37:46So don't be
37:47I say this always.
37:48Don't be um yeah, master one tool.
37:51You have to to to um to understand the processes, to have the mindset of an analyst or engineer.
37:58Yeah.
37:58And I think what you say there about
38:01tools in the twelve years that I've been working in analytics, I've seen probably, you know
38:09uh two or three big pivots in how people think about analytics technology.
38:15However, every single one of the companies that I've worked at is still doing the same thing.
38:21They're still selling the same products.
38:23Still selling the same capabilities.
38:26Yeah, maybe they have new customers, but the fundamental challenge, the core challenge is still the same.
38:32What changes is how they solve that problem and what new questions they ask and what new problems they solve.
38:37So if you learn uh let's say Tableau or Power BI, people people asking which one should I do in the comments?
38:43I'm serious.
38:45If you learn tablet power, yeah, well, that's great.
38:48But what you're actually learning is the underlying skill.
38:52The tools make you learn their terminology for a certain activity.
38:57So what you need to learn is
38:58What is it that I'm actually doing?
39:00I'm transforming, I'm modeling, I'm shaping, I'm creating calculations, measures.
39:04Understand the underlying concept because then when another tool comes up, let's say Sigma or whatever data bricks.
39:11You can just take that knowledge with you to that platform and ask, well, how do I do that in this platform?
39:16And in the future with AI
39:19workflows are changing.
39:20So the way we work is changing.
39:21But still the fundamental thing you'll do, the way you do the analysis, probably won't change.
39:26And so
39:27you still need that fundamental understanding of what is the problem and what problems need solving.
39:32So you can drive those workflows, you can build those workflows to solve the problem.
39:37Um, so I I'm I'm very much of the opinion that whilst I think our jobs and our workflows will change, I think we'll still be fundamentally at the driving seat.
39:46We'll just be doing it differently.
39:47So if you want to be at the forefront of that change.
39:51You need to be challenging yourself to explore the new ways of doing the things you've already been doing in this new context and seeing where the opportunities are and you know challenging your senior colleagues.
40:02Your senior colleagues will look at you and expect you to come to them with these innovations.
40:09If you don't, what they do is they look outside of the company to bring the innovations in.
40:13So really seize that opportunity, right?
40:15Sei that opportunity to be that person that really challenges the way the company does things.
40:20And you have to start by understanding the problems again, um, as we've said.
40:24So yeah.
40:26Um now since we are talking about tools, I know that question came from the chat.
40:31Power B I and Tableau, you decided a big decision on the title.
40:36Or the channel name called Tableau Timmo.
40:39Now I think it is data with tablotum.
40:41Tabletim, yeah, yeah.
40:43Now
40:44Why you choose to originally.
40:48So I have this belief that um
40:53I it's hard to remember people if they don't stand out.
41:00And so I could have done data with Tim.
41:04I thought about this actually for a long time.
41:06I could have done data with Tim.
41:07But the thing is, I I genuinely felt like a fraud if I wasn't talking about anything other than Tableau and Or Tricks, to be fair.
41:17I I I knew enough about other tools, but with Tableau, I genuinely felt I really knew this concept.
41:23And there's this thing, I think maybe it's just pride, where if I'm gonna teach someone something.
41:28I need to be so confident that I I'm maybe one of the best people at teaching it, right?
41:35That's this like sort of complex in my head.
41:37And so I was like, yeah, I think I can be
41:40one of the best people teaching Tableau.
41:42So that's that's why I went around Tableau.
41:45Now the funny thing is it's it's not the mo it's not not the tool I use the most.
41:49at at all.
41:50Like it's not the thing I use.
41:52But I I decided to mold my identity around Tableau and I just thought I think
41:58That's what will kind of cut through the noise and say, hey, if you want anything with Tableau, come over here.
42:04So I started doing that.
42:05And I started doing it in a different way.
42:06There were lots of Tableau blogs.
42:08Tableau community is very um, let's say, creates a lot of content.
42:12But no one was doing videos and no one was doing videos of a quality that I wanted to watch, right?
42:18Like I I sat on YouTube watching, you know, 4K, 1080p, wonderful, crisp videos, and I was like
42:25Why isn't anyone doing this with tablets?
42:27Surely it can be done, right?
42:29So I set about doing it and I discovered it was hard, but I just kept on doing it and eventually
42:34I started a workflow and it it worked.
42:36And so yeah, that's how it started.
42:38It's really no more intentional than that.
42:41YouTube that you once wrote a high quality content.
42:44Off the tab floor, right?
42:46I remember this wording, right?
42:48Yes.
42:48I used to have in the banner high quality tablet tutorials.
42:52So I I as you say that I remember this because once I was designing banners and I was like getting inspired again from my mentor, yeah, and I saw high quality, uh this guy
43:04wants really to change the game, you know, because yeah there is a lot of content where you say, you know what, this is not really high quality, I would I would say with the intro, with the outro.
43:14It's like someone sharing screen.
43:16Uh go through the topic and that's it.
43:18No summary.
43:19There's no story behind the video.
43:20It's like, oh, the audio is very bad, or 4K.
43:26And uh yeah, I thought uh this guy wants to to make it high quality.
43:30So exactly now if times goes back, you're gonna
43:33Pick that name again, Taplo.
43:35No, I would not pick that name again.
43:37Um if I was starting a YouTube channel today, I don't know what I'd pick because there's lots of
43:44YouTube channels now that you know use some sort of combination of whatever.
43:48I think I would just say data with Tim.
43:51I just rely because I think what I have to offer today is my experience in the industry.
43:56But people know me.
43:58People have come to know me.
43:59Whether they use Tableau or not, I think they just know me as Tableau Tim.
44:02So the big challenge for me this year and in the future is to try and really push into this.
44:07really challenging space where can this person who's a you know knows Tableau inside out also teach you all these other things?
44:14And that's essentially, I think I can do that in my own little way.
44:18Always be Tableau Tim, but actually happily use Power BI or happily use Sigma, whatever other tools people want to learn.
44:25So yeah.
44:25Um
44:26I just want now of course to turn this to tool discussions, but let's give a quick summary from your point of view about those two tools.
44:34Yeah.
44:35Maybe I'm gonna give my maybe start you.
44:37Maybe start with your opinion absolutely.
44:40Tableau and Power PI, I think, are they're often compared, but I don't think they are um
44:50comparison tools.
44:51I think they overlap a lot, but I'm not sure they are direct comparisons.
44:56Where they are different
44:58is I think their philosophy of how they go about creating and managing assets.
45:04Power BI is very connected to the Microsoft technology stack.
45:08Whereas Tableau pushes to be, you know, let's say platform agnostic.
45:14There's an asterisk around that because Salesforce, but anyway, we'll come back to that some other time.
45:20You know, Ta Tableau genuinely tries to connect to everything equally in a very logical way.
45:26The other way they're different is I think Power BI has a much more it the philosophy around
45:33how Power BI is deployed makes it much easier to get into a business um very quickly, very widely, without having to be, let's say, emburdened too much by licensing in specific ways.
45:47Whereas Tableau has this sort of very difficult hurdle where to get it installed, you have to make sure you're on the right version.
45:53You have to have cloud or server, all these little things, and there's all these little add-ons, just very difficult sort of pricing structure to understand.
46:01And so when people often compare the two, what I think they're actually comparing is not the platforms, the whole entire platforms.
46:09They're just comparing Power BI desktop and Tableau Desktop.
46:13That to me is 100% of most comparisons when people talk about those two tools.
46:20But if you then start to bring in the platforms and the ecosystem, then I think they go further and further away from each other.
46:27And they're actually both very good, you know, tools in their respective fields.
46:32Again, if you're very closely aligned with Microsoft and you don't have a tool today, I would start with Power BI.
46:37Very easy, very good to set up.
46:39If you decide to evolve, you can grow very easy on the Microsoft platform.
46:43If however you're not wedded to Microsoft, you can go to the Tableau ecosystem and pick your own sort of infrastructure.
46:49But
46:51I think there's one thing which I think Tableau is somewhat a little bit more, let's say, um, this is an opinion, by the way.
46:58I should say this.
46:59I think Tableau is slightly better when it comes to what I would say the um, you know, artisan.
47:05uh polished product, you know, really high levels of design, um, lots of flexibility, lots of chart flexibility.
47:14Tableau has, I think, really nailed that pattern down.
47:17It's not to say that Power BI can't do those things.
47:19It's just a little bit more fiddly in Power BI compared to um Tableau.
47:23And there's some small things philosophically, but fundamentally
47:27You know, five years ago BI was not a commodity.
47:30Today it is.
47:31And so all the tools pretty much do the same things.
47:34And so, you know, maybe over time that's changed.
47:36But yeah.
47:37And that's sort of my
47:38Sitting on the fence answer.
47:40It depends.
47:42Of course.
47:43By the way, guys, if you want to be an expert in any field in the tech, always start with it depends.
47:49Yeah.
47:50All the answers, like in any meeting.
47:52You can ask me any question now.
47:54Like I can go confident to any meeting, to any place, and someone asks me a question.
47:59I start always, it depends.
48:02So never give like yes or no, always it depends and then explain both of them and the manager gonna get confused and
48:10It is And then you have a hand and you welcome to the decision.
48:13Many many managers hate this, hate this.
48:16Yeah.
48:16Don't say it depends.
48:18I we always say it depends.
48:19Once you get really some senior level on at your work, let's say you know exactly how things there is no like yeah
48:28Let's say black and white.
48:29There's always depends on the scenario, depend on the project, depend on the company and the country as well.
48:34Yeah.
48:35So that's why it really always depends.
48:38I can't like maybe I can tell you my experience about this because I had
48:43Um yeah, I had a lot of discussions, let's say, about this.
48:46First of all, I was really surprised about that everyone is talking about this comparison.
48:50I know that is important topic, but actually at the end, at the work
48:55You don't need to compare those things because usually the company can decide on those stuff.
49:00And mainly it's gonna be decided on the money, on the licenses, on the sales, whether they get a good contract with Microsoft or not.
49:09So yes, we can give our opinion at the word, but it is not something that you have to master.
49:14Uh this is something that I see a lot, a lot of content, LinkedIn posts, videos.
49:18Power BI uh tableau and stuff.
49:20This is something that you don't have to master.
49:22It's something usually the principal architects or let's say the senior let's say uh people at the work
49:29Maybe the sales, they're gonna decide on this other company and you have to live with this tool.
49:34Now, I can tell you here in Europe or at least in Germany, we use a lot Microsoft Azure.
49:41as a platform.
49:42Yeah.
49:42And that's why you're gonna see most of our projects here in Germany gonna be with Power PI.
49:47More than simple.
49:48It's not it's not that popular.
49:50And that's because of Microsoft.
49:51It's easier to integrate Power PI with the Azure
49:54So that's why here it is almost every project is PowerPI.
49:58Yeah.
49:58But maybe in USA or different countries depend which cloud they are using.
50:03So they might start utilizing Tableau.
50:05Or Power BI, but here it's like the standards, yeah, becoming like this.
50:10And um for me, I can say you can use actually depends on the company of card, you can use both of them.
50:16Because especially in big companies, now I had one project where I had both of them in my projects.
50:22Now I had always like sectors in from or let's say I segment my customers into sectors.
50:27Like
50:28I'm gonna say huge amount of customers gonna be standard users.
50:32They would like standard reports.
50:34They're gonna like every day gonna check an operative report.
50:38So they're gonna click on it, see whether there's an issue, and that's it.
50:41Those people are gonna have standard QPI reports and it is more than enough to use PowerPI for those use cases and as well it's easier for you because you don't have to manage licenses and stuff.
50:52So you don't want to give three thousand licenses just to have an operative report, yeah.
50:58So that's why majority of people that using those
51:02PI report dashboards, it is more than enough to have power BI.
51:06But you're gonna have in some scenarios some key
51:10Let's say business people that would like to go deeper in the analysis.
51:14They would like to make some advanced questions and stuff that is really advanced, and you're gonna hit the limit of RBI very fast.
51:21Especially if you are making some some lit advanced visualizations.
51:25Like for example, we had some dot plots.
51:27If it's more than three thousands, you're gonna get the limit of RBI CA, you cannot do that.
51:31So there's a lot of limitations.
51:33And Tableau allows you to do things unlimited, yeah, especially with the data points.
51:39So there will be some scenario where you're gonna have maybe 20 or 10, depends again on the projects.
51:45We're gonna have people that want advanced things and they they really challenge you, yeah, with the visualizations and you're gonna hit the limit of power BI, and that's why
51:54I end up having like 90%.
51:56Everyone is using Power BI, but only for those users.
51:58We make special projects using Tableau and we offer those advanced visualizations.
52:03At the end, both of them are using the same data lakehouse
52:07Exactly.
52:07So the same data is used in both of the tools.
52:10Yeah.
52:10But I would say for standard reports, don't overcomplicate it.
52:14If you have already Azure, then just go with the Power BI.
52:17Yeah.
52:17Now my recommendation from my side, if you want to learn one of them
52:20You have to understand yeah how things work at your country.
52:24If you are want to target here Germany, so for example, you want to work here in Germany, then I would suggest to start with PowerPI and then
52:32I think it's you're gonna spend like a week or two weeks just learning Tableau.
52:35It's really fast.
52:36Once you have understand one of them, then so this is actually my take on it.
52:40to be honest my yeah about Tableau and Power BI.
52:44It's really as at the end depends, yeah.
52:46Yeah spot on, spot on.
52:47I think this point you make about um purchasing decisions, it's it's the biggest driver and
52:53Uh you know, the CFOs, CIOs, CDOs, you know, chief information officer, chief data officer, chief financial officer.
53:01They make decisions sometimes under pressure because they've been asked to do something.
53:08And so
53:10Uh a good decision can sometimes not make sense to an analyst in that sense.
53:15So you just have to factor that in.
53:19Nice.
53:21Um Tim, we are like I I understood there is a lot of people in uh the channel or let's say from the comments that a lot of people are starting
53:32their career now and they would like to be a data specialist.
53:35So or some people are switching from one career to another.
53:39And I got a lot of questions about how to become a data analyst and how to become um
53:43Let's say what I should learn now.
53:45So maybe you can give from my your point of view, if now times goes back, how are you gonna learn
53:52all those skills to become now Tim again as a data analyst.
53:55How are we gonna do it fast?
53:57Because there's big confusion, let's say, about it.
54:00And I would like to hear your opinion.
54:04Yes.
54:05Um this is gonna be a hard one, I think, for most people to um let's say accept, but it's time.
54:16Um
54:18I appreciate that, you know, when you want to learn something fast, uh, being told to be patient and just take your time is not
54:27something you want to hear.
54:28But let me let me play it out to you why time is actually the secret thing here.
54:33And and it goes back to um the way skills compound over time.
54:38Okay.
54:38So when I when I learned Tableau on day one,
54:41I knew very little.
54:42I thought I knew a lot, but I knew very little.
54:44I did a like a 10-hour course.
54:46I did a certification within one week.
54:48I thought, you know what?
54:49I know my stuff.
54:51Look at me.
54:51I'm out, I'm out here consulting.
54:53I go into the client and the client shows me how to do this thing with a filter action and I'm like, what is a filter action?
54:59And I was like, I managed to pass a certification without knowing what, without knowing, uh, not knowing what a filter action is.
55:06So I blew my mind.
55:07I was like, what do I not know then?
55:10So then I just pay started paying attention.
55:13And here I am 12 years later.
55:14I'm still learning Tableau.
55:17But here's the thing.
55:20Each time a new release came out, each time a new feature came out, I just learned it along with my day job
55:27And over 12 years, I think I can confidently say I know the platform very, very well because I have been able to just slowly and incrementally build on my knowledge over the last 12 years
55:39And so if someone's learning Tableau today and they want to be have as much experience as me, it's almost impossible because I have this massive advantage.
55:48I've had 12 years to learn what I know.
55:51And it's the same with anything new.
55:53When you learn it for the first time and you do a course, you will enter the topic.
55:57But then you just have to respect that everything that comes after that just takes time, experience, opportunities.
56:05And it can sometimes feel like maybe the opportunities don't come your way, maybe the chances to learn and try things hands-on don't come your way.
56:14But nothing can beat the power of you just spending 10 minutes every single day slowly adding to your knowledge, slowly adding to your knowledge.
56:23to the point where over time it compounds like a bit of a a savings account, right?
56:28It it just builds up to a point where your knowledge becomes so obvious to people.
56:34that they realize that you're under underutilized or you're over skilled sometimes you hear people say.
56:40And so that's the biggest asset.
56:42Time, time, use time to your advantage.
56:45Be really realistic about the time it's going to take you to become not just good at a topic.
56:51Don't just try to be good.
56:53Really, really try and be one of the best.
56:55It doesn't mean you will become the best.
56:57But try to be one of the best.
56:59And if you just pay attention to like what is it the people who are the best at something do, they pay attention to all the details, all the little details, all the menu options you've never thought to ask questions about.
57:09What does that do?
57:11What no, what does it really do?
57:13When I do that aggregation, what actually happens to the SQL query that goes to the database?
57:19That's the level of detail you need to think about.
57:21Because when you understand that, then suddenly your knowledge just flies through the roof.
57:26Things you didn't understand before start making sense.
57:28Your brain connects the neurons.
57:30Connections make get made across different products.
57:33You see a concept, your light bulbs lights up.
57:36Oh, I know about that already.
57:37And then now you're running.
57:39Instead of walking, you're running.
57:40And then instead of running, you'll be flying.
57:42And that's what time does.
57:43Um, but you just have to keep at it.
57:45A lot of people give up too quickly and too easily.
57:49You've just got to keep going.
57:51And I know it sounds crazy to say that.
57:53Just keep going.
57:53But it's genuinely that.
57:56You know what, uh Tim?
57:58I was reflecting on my forty years.
58:00Uh what what did the like the first tip that I'm gonna fill in my video
58:04Yeah.
58:05I was like sitting and writing down stuff, ideas and I like the tips that I would like to say
58:12And it was really hard for me to say, you know what, what is the first one, the first one that I'm gonna say.
58:16And that was exactly what you just mentioned.
58:19Everything takes time.
58:21There is like this is the best thing that I have learned
58:24during like my last 14 years.
58:26Yeah.
58:26Everything.
58:27Not only like learning Tableau or becoming data analyst.
58:30Everything really.
58:32Anything that promises you to get something fast, it is fake.
58:36So as like you said it wonderfully and I made it my first thing that I want to mention my video.
58:42Everything takes time.
58:44Your body, your skills, the money, um everything.
58:48Don't rush it.
58:49Don't rush it.
58:50Do it slowly.
58:51And I don't know anyone that's really kept doing what he's doing and he didn't succeed at the end.
58:58All had at the end jobs, we all get hired.
59:01Just keep going.
59:02I don't know anyone from like yeah colleagues or from university times that didn't get hired.
59:09They all studied, they all kept pushing at the end get hired and then
59:13starts doing maybe something else later.
59:16So just give it time, don't don't panic.
59:19As I was student to be honest, T
59:22The number one fear that I had in my head, like who gonna hire me?
59:26Because I didn't believe myself and I was thinking, okay, I'm learning a lot of things in university, like who gonna hire me?
59:32But
59:33Look at it.
59:33I left Syria.
59:35I came here to Germany.
59:36I studied.
59:37I went to one of the top companies here in Germany, like Mercedes Spence considered to be one of the top.
59:42I worked with brilliant people and I led project at the end.
59:46It was
59:47Like uh just give it time and wonder gonna happen.
59:50So I hope that's don't yeah, I didn't rush it.
59:52I didn't trust just give it time.
59:54The same thing for YouTube.
59:55Let's go a little bit to YouTube.
59:57I started like, I don't know, one year, Tim, I had like 10 views or 20 views.
60:02I didn't rush it.
60:03I did I could like pay for it.
60:05I don't know, pay ads and push more and maybe buy some uh yeah, I don't know, buy things.
60:11But I didn't really care.
60:12I made one video a m a m a week or two weeks.
60:16Put it.
60:17I know whether the like I
60:19I try to bring good quality but sometime the video is not that good, but I just push it and keep going.
60:26Over three years
60:27I would never be like I would never expect this that I left my job just to do YouTube.
60:33Like if you ask me three years ago
60:35I would expect that I'm gonna get my hair gray at Mercedes Pans and I would never leave my project.
60:42Those are the colleagues that I'm gonna spend, I don't know, next 30 years.
60:47Doing those projects, I would never expect this.
60:51Yeah.
60:52It's wild, isn't it?
60:53That's right.
60:53It's wild.
60:54And you've got so much momentum.
60:56Alec.
60:56I'll I will say this to everyone watching.
60:59Just like Barrow is just getting started.
61:02I keep saying this to people, like you don't understand the momentum you've got and the way that you set yourself up.
61:11I know from a content creation perspective, like I keep rubbing my hands because you you're just getting going.
61:17Like everything you're doing now, I always look at it and I say, you were already doing this level of quality of content before.
61:23So I just think
61:25Give you a year working on your own stuff.
61:27Just how much more can you do?
61:29And again, it takes time.
61:30It takes time to set up these processes.
61:32It takes time for you to transition.
61:34But this I kid you not, this man is gonna absolutely fly out of YouTube in a second.
61:42Uh you'll you'll easily be one of the biggest data creators uh on the planet.
61:46So just keep as I've said to your audience, you keep going, man.
61:50You're doing such a fantastic job.
61:52Man, you are you are the biggest supporter or mentor of this.
61:55Thank thank you.
61:56I I now I'm stressed.
61:58Now now I'm stressed out.
61:59Now I have to deliver because of
62:01Don't say that.
62:02Now people are gonna do that.
62:03I'll be messaging you on WhatsApp, guys.
62:05Come on, Barry.
62:06Where's the cam?
62:08They are already pushing on me crazy on the comments.
62:11Like, hey, where's the PySpar course?
62:13I would like to have, I don't know, pandas.
62:16And I was like, oh my god, I I would like to deliver everything, but I I'm trying my best.
62:20Um yeah, but I would never expect that my career could take this shift.
62:25um Tim.
62:26Is this something new that's gonna happen now that the experts can start their own channels or they start making their own product?
62:33Because I was like I had this mindset.
62:36I I
62:37Went inside Marcilla Spence and many people tell me you are really lucky and I don't know, yeah.
62:41They gratulated me now you are inside forever.
62:45Because one manager told me people like joined a company with black hair or maybe Germans has yellow hair.
62:52Yeah.
62:53They are blunt and they leave with the white hair.
62:55So what are you doing while you are leaving?
62:58So I thought that maybe I'm gonna be a manager, maybe I'm gonna be a team leader, or maybe I'm gonna be senior principal, that architect.
63:06But I would never expect that I left everything and now I'm just doing YouTube.
63:10Do you think this is something that's gonna be a new option for people?
63:13Because it is really very
63:15It's not that easy, of course, to make YouTube channel and to grow this, but it is possible.
63:20Like at the end it is I'm not doing magic here
63:23But I think this is really option for professional people now, especially at those times, you know?
63:28Yeah.
63:29It's it's there is definitely something different happening around the way knowledge is shared.
63:35Okay.
63:35And it's difficult because what I would say is, whilst it's still true that things like, you know, textbooks, course platforms, all of those things still exist.
63:46What they do very badly at is keeping up with modern trends.
63:52Like you would never have learnt data engineering at university because it would not have been like
63:59uh a skill that was evolving fast enough for the academia to keep up with the pace of the industry is going.
64:05So you did you did the subject, but what you learnt at university was nowhere near keeping up with the tools and the industry and the practices, right?
64:14And as a result of that, there is always this gap for people who are in the jobs doing the work to teach the next generation
64:23How to do the work that has yet not been defined.
64:26Yeah?
64:26So there's there's always going to be this gap for people to teach other people, the things that don't have names yet, the things that don't have roles yet.
64:34And because of that
64:36You will have a constant need for people like us to say, you know, I I I get on YouTube and I say, here's what's new in Tableau.
64:44It's a very small niche, but I try and help keep people up to date with Tableau.
64:48What you're doing with data engineering and analytics in general is you're bringing people up to date and really bringing them into this career.
64:57I'm sure there's tons of, you know,
64:59people starting their careers watching your content and they're using it as a way to get in the jobs.
65:04I've seen the post, right?
65:05And it's it's something they couldn't get through a textbook.
65:08They couldn't get it through a structured course platform.
65:11They couldn't get it through university, their parents couldn't teach it to them, the school couldn't teach it to them.
65:16There's only one way they're gonna learn it, and it's through people like yourself.
65:19And I think there's gonna be an even bigger need for that as the world gets faster and faster and faster.
65:26So yeah, definitely think it's here to stay.
65:29I I I believe this gonna be exactly like a new path that experts gonna like try out over the time because
65:39Once you join a company, you know, and you are you have a lot of energy and you want to do project and stuff, you're gonna hit the limit.
65:44You there is soft cap at the work where your salary is gonna stay the same.
65:49Uh you cannot expand more, like this is your project, you cannot do more.
65:53This is like you're gonna hit a roof, you know.
65:55And sometimes some people would like to do more, you know.
65:58I would like to work more than 40 maybe hours a week.
66:01Yeah.
66:02And maybe I want to build my own business and stuff.
66:04So this gonna be, I think, um maybe a new trend.
66:07I convinced by the way, Tim, one of the guys at my work to start YouTube channel and two weeks ago
66:13He did start one.
66:14I don't know whether you saw the uh the last live streams.
66:17Yes.
66:18Simon.
66:19Simon is consult data engineer consultant and he uh started YouTube channel two weeks ago and
66:25This guy is brilliant one.
66:27He's German.
66:27He gonna like start as well talking about that engineering.
66:30So I thought maybe over the time I will be the guy that is motivating other experts to to start publishing.
66:39Because
66:39Yeah.
66:40To be honest, Tim, three years ago I had LinkedIn, but I have only one image, and you can see nothing in the LinkedIn of my profile.
66:47I didn't list my skills.
66:48I didn't do anything because
66:50I know I can get hired easily between the next jobs.
66:54I'm gonna just I have my connections and I can easily find a new job.
66:58So I don't need the whole LinkedIn.
66:59So I had only one old picture.
67:01And stuff like that.
67:02And I know many experts, they are not in LinkedIn.
67:05They are not sharing any word.
67:07They are like hidden, hidden gems, really.
67:09And
67:10And if they start like slowly publishing things, this is gonna be amazing.
67:14And I'm trying now my my best to bring them as well.
67:18And uh to follow as well you.
67:19You motivated me as well.
67:21Yeah, I start publishing those stuff and you
67:23Like pushed me and to tell me, yeah, keep doing what you are doing.
67:26This is amazing and stuff.
67:27So I think it's gonna be in you path.
67:30It's not only you're gonna be a manager, project lead, or senior data analyst, data engineer.
67:36You could be as well a content creator.
67:38Once you have a knowledge, you can share this knowledge.
67:41And as well, you I'm not like I'm gonna say it's gonna be for free.
67:44You can do free things and as well you can sell things and you can live from it.
67:49Yeah.
67:49Uh so I think this is gonna this gonna be brand like new trend, maybe in the data world, especially now, yeah, with the with the
67:58situations yeah with the economy now that is really hard for the companies to keep up we know with raising the salaries and the bad economy that we have.
68:08So now um Tim, I'm gonna ask you about AI.
68:13What do you think?
68:15Um yeah, it's of course a big question, but we can speculate a little bit now about AI.
68:19Yeah.
68:20Are you afraid about it?
68:21Do you think nav after ten years AI gonna like replace what Tim is doing now?
68:27Or
68:28You're gonna like find your own way and what yeah, what's gonna be your work in the future?
68:32How you can imagine it, you know, in 10 years.
68:35Because it's scary, yeah.
68:36Still scary for everyone.
68:38The boundaries are still not very clear.
68:41And by boundaries, I mean ethical boundaries, uh, the way we use it, where we can use it, how to use it, the tools that can use it.
68:50All of those are still being
68:52worked out.
68:53What I'm certain about though is that there are already some things we do today where AI
69:00can help us do our jobs better.
69:03There's one area that I've I've I'm telling everyone to start thinking about it in this way, which is in our jobs.
69:10There's often this challenge where we need to be able to try things quickly, but the things we want to try are not quick.
69:18A simple example, I want to prototype um a chart.
69:22And you might think, well.
69:24Why don't I just use one of the existing charts available in Tableau and Power BI?
69:28But you might be visualizing a concept in the business.
69:32It's actually quite difficult.
69:33You talked about an example where you you took the factory map.
69:37and you took an image of the factory and you put it into Tableau.
69:40So you used an image and you created something.
69:42Okay.
69:43That's one way of doing it.
69:44But imagine you wanted to prototype uh a solution that didn't start in Tableau or didn't start in Power BI.
69:51What could it look like?
69:52And what could the solution be?
69:54You know, a year ago, I would have said to you, oh, this is not worth investigating time.
69:58Let's just try and take an off-the-shelf solution.
70:01But in today's world, I've I've seen a couple of cases personally.
70:04Where I've been able to prototype things in two hours that would have taken maybe a week with a developer, me having to go back and forth explaining things to build exact same thing.
70:15So within two hours, I'm able to do something that I know would have taken a week
70:18with a very skilled developer.
70:20And what I'm prototyping is not shipping a product.
70:23It's simply this exploration of if I was going to solve this problem
70:28What could it look like and what does it take?
70:30And you might think, well, how is that useful?
70:32Well, when you're coming up with a requirement for these solutions, it's sometimes hard to
70:38come up with good requirements unless you've actually used the end product.
70:42And I know it sounds bizarre, but sometimes you do need to go and build this sort of really broken thing to understand, okay, so if this is going to work, I'm going to need this, I'm going to need that.
70:52And AI has become this really nice tool where I have it sometimes open and I I just talk to it back and forth ideas.
70:59It's like if I was gonna do this.
71:00How would I do this?
71:01Okay.
71:02And I can think, I can really think much faster because I'm going through ideas and concepts much faster.
71:08And every single day
71:10Two, three times a day, there'll be something that comes up in Claude and it tells me something.
71:15And I was like, I didn't think about that.
71:17That's such a good idea.
71:18And so now I'm I'm an expert.
71:20I know my stuff.
71:21So I'm I'm taking that idea and I'm like, right, yeah, what if we did it this way?
71:24I'm in Tableau doing that way.
71:26So AI is already a capable tool.
71:29And it's really hard to frame this to people because unless you've experienced this yourself, it's really hard to explain.
71:35But I think in five, six, seven months, people will be building small personal tools in analytics.
71:41So maybe you do something every single day in Python and other some other tools.
71:46You might get to a point where you can build a tool to do that thing for you.
71:49You're not going to run it with AR.
71:51You're just going to build the tool that does something in a deterministic, predictable way.
71:56And then you might explore how to take that idea further.
71:59That will be the thing that comes next.
72:00And then your teams, other people working in your organizations, the quality of the way they take notes, something even as simple as that, like you know, transcripts and stuff like that.
72:09You know, even our YouTube transcripts, you probably know this, right?
72:12Like suddenly, like people in any language can watch our videos.
72:16Ten years ago, that was that was not possible, right?
72:18And so all these small things, like learning, like time.
72:24They compound and there comes a point where there's so much uh change in these small things that adds up to make a completely different uh way of working.
72:34And that's the thing you don't want to miss out on.
72:36So um
72:38I'm very confident AI is going to be coming to all our work, but I think you have to be deliberate about discovering where the boundaries sit in the work that you do.
72:47challenging people around you to try and find those boundaries in ethical, safe, you know, governed ways in your businesses.
72:55And then just explore what you can do, what you can make out of it, what can you learn?
73:00How can you try it?
73:01And um you might think, oh, these, these, you know, these tools are expensive.
73:05Yes, I know.
73:06Um, you know, $20 a month for that and $20 a month for this.
73:10Just pick one.
73:11Just invest in it for one month.
73:13Just try it really, really hard.
73:15Um, and I do say invest because the free versions are very limited.
73:19They're very limited compared to
73:21the paid versions.
73:22And with the paid versions, you really start to see, okay, this is how this can work.
73:27And once you have that model, it's much then easier to justify the investment and the time.
73:32And it can be a great learning tool as well.
73:34So again, another on the fence answer, but yes, it will change our jobs, but I think we have to be the architects of how that works.
73:43And we only do that by
73:44trying the tools and uh really discovering where the boundaries lie so we can we can build it into the way we work
73:53I would say um this is exactly the mindset, yeah.
73:57You have like I see that you are not scared about it.
74:00You are let's say
74:01Happy.
74:02Let's see.
74:02You have now extra tool that's gonna assist you.
74:05And I believe um like from my point of view, I think them there is a big, yeah, I would say
74:14Big um yeah.
74:21And I think this is
74:22Maybe some fake promises that they are getting about it.
74:26Because um I still believe we have a lot.
74:30Like if you worked a real project, how am I gonna say it?
74:33You can understand the struggle, how hard the business is and how complex things are, how old the systems where they are generating the data using it.
74:41So you cannot just play and play an AI and it's gonna do the whole thing, the whole data engineering and understanding the business.
74:48And I can tell you the AI didn't learn yet from
74:52let's say company's data, yeah.
74:54It's learned only using public data.
74:56And most of companies data are are protected
75:00And as well as you say, yeah, it is in the mind of people.
75:03So most most of the domain knowledge actually are not documented in documents or let's say it is written and AI can learn on it.
75:12It is in the mind of people and that's why I
75:14From what I saw, things gonna take really time until you have only AI that is doing the whole analytical process end-to-end.
75:24My friend still here in many companies, they are still using on-prem systems, very old tools.
75:31still still a lot of companies are not yet there having a clean data strategy for their company.
75:39So there's a lot of like a really long way until you have fully AI-driven company.
75:45or data company, you still have to uh there's a lot of manual work.
75:49There will be a lot of things that needs a data engineer and need the data analyst.
75:54And I believe it will just speed us.
75:57Like if I look to my backlog
75:59six years or seven years ago, it was always full with ideas and stuff, and we didn't have the time to do it because we are busy with only few tasks.
76:08Now with AI, maybe I'm gonna have
76:10implemented all those new ideas, you know.
76:12Yeah.
76:13So that means it's gonna speed us and they will be always work for us and
76:18I'm sure if you are in a company, you're gonna find your way with the AI and you're gonna use it in order to improve your work.
76:25But I'm gonna say as well, it is hard for people to, let's say,
76:29find a new job because of two things with the AI hype and as well the bad economy that we have.
76:34Yes.
76:35The hiring now is really frozen.
76:37And I totally understand the struggle that people having now we are finding new job.
76:42Like now for juniors, it is early.
76:44I can understand the struggle that companies having this mindset now.
76:49We're gonna hire only seniors.
76:51And of course, how are you gonna get seniors if the juniors are not working, you know?
76:56So that's why I think there is some fake uh expectations about this.
77:01Um if you are a junior or let's say you didn't hit years yet your first job, you have to push harder now.
77:07The limit, the expectation is way higher.
77:10They expect now from juniors to be seniors already.
77:13So now by just having knowledge about few skills, it's not enough.
77:17You have really to push harder, to make projects, to to understand, to learn how to think like a senior and
77:24Ready to push more to get hired.
77:26And once you are inside a company, I'm gonna say don't worry about it a lot because AI gonna speed you up and
77:33And it is a positive thing.
77:34So I was really happy to see all those AI things and I was an AI engineer.
77:38I thought, sorry, as a data engineer, I thought, oh now I can do the review process of the code very fast.
77:43I don't have to check everything on like the whole day.
77:47Approving pull requests, I can now let the AI checking the code, whether everything is fine, whether there is any security issues, and I can do the review in a few minutes.
77:57And I can be faster in the project.
78:00So it's only hard from my point of view just to enter any company.
78:05But once you are inside, you're gonna live the transition.
78:08I can tell you
78:09As well, I was ETL developer before Tim, or as well BI developer.
78:15And until I built one visual, it took me a few months because the old tool, I don't know whether you experienced before Tableau and Power BI.
78:23we had like micro strategy and old like some some tools where the process is painful you have to build a model you have i don't know to define the measures the dimensions yeah like before you hit the first visual it takes you few few months
78:38And now with Double and Power BI, you are very fast.
78:41Yeah.
78:41So that's why those tools gonna improve us, gonna make us spe fast.
78:45And uh I'm as well happy about it.
78:48It's improved me as well in content creation.
78:50You know that already, yeah
78:51How we make videos, how we edit, and and the whole process.
78:54It's a it's a force multiplier.
78:56And I think when you really think about that, force multipliers are doing one thing.
79:01They're
79:01Amplifying your creativity, your up your opportunity to reach new things and your opportunity to push things out
79:09But the critical thing is it can't multiply anything if you don't do something, right?
79:13Like it can't if you don't try them, if you don't sort of try, they can't they can never help you.
79:19So
79:21Everything comes back to how you frame the capability.
79:25You have to explore it.
79:27I'm not saying do something you're not comfortable with.
79:29Explore the things you are willing to try.
79:32Like maybe it's image generation, maybe it's uh a transcript or meeting notes.
79:36Just try something small.
79:38And then start to explore the bit that makes you comfortable.
79:41And as you do that, evolve your thinking, read, read, read, read, read.
79:46Like it's so
79:47There is so much content out there where people are thinking in public about AI and sharing their thoughts.
79:54And it's a really fast way for you to
79:57um become someone senior in this topic in a real in a very real way.
80:02So you know, read newsletters, read articles.
80:06People are writing essays on Twitter or X now.
80:09These are all opportunities for you to get an insight into the way that some of the brightest people are thinking and therefore how you can borrow inspiration as we started this video, right?
80:20um to build on yourself and build your own career to become the next, you know, person in this industry
80:28Yeah, I totally believe on that as well.
80:31Um Tim, um now about content creation, I know this is hard to process.
80:37Yeah.
80:38Now
80:39Do you recommend it for people that have family?
80:42They have already worked?
80:44I know that is something like for me it is easier for me because I don't have kids.
80:49I'm just married.
80:50But for you, you have three wonderful uh kids.
80:54I I um uh I adore them
80:57You send me the uh Christmas photos of them.
80:59They are they are wonderful.
81:02So now how do you manage still to make content, to come now with me to talk live?
81:07You know, we are already more than one hour and doing as well your job.
81:11Yeah.
81:12Because I believe some people now would like to try this out.
81:14So how do you manage that?
81:20It's gonna sound weird.
81:21It's an it's an answer everyone knows.
81:22It's gonna be balance.
81:23You know, we hear about
81:25work-life balance, but what it means for different people is actually the most important thing.
81:33Um
81:34I've had the opportunity to build up my career in such a way that I've had the flexibility to choose
81:42And I think the biggest mistakes you can make in this are you take on too much.
81:48Yeah.
81:48And you take on too much by not allowing yourself enough time to understand
81:53Whether everything that's on your plate is currently good for you.
81:56So in my shoes, I started with my career like 12 years ago.
82:01Um, I only met my wife uh like six years ago, right?
82:05So um
82:07I was in my job just just just working.
82:09I had a dog uh as well along the way.
82:12So the the first
82:15Member of my family was my dog eight years ago.
82:17Um and then I met my wife.
82:20She joined the family, and then we had kids and then everything else.
82:23And all that time I've had a career that has enabled me to have a dog from a puppy.
82:28uh meet my wife, all of that stuff.
82:31And it's fundamentally because I've worked from home.
82:33So when we talk about work-life balance, the most critical decision you can make is
82:38the first decision.
82:39And for me it was doing a job that allowed me to work remotely and work from home.
82:44A lot of my clients were very happy for me to work from home and then COVID accelerated that.
82:49And I've always worked from home.
82:51I know everyone doesn't get that flexibility.
82:53Maybe you have to go into an office.
82:54I did work in an office for two years of my career.
82:57And so in that instance, I made different decisions.
83:00And I've been making content this sort of whole time.
83:02It's not like I I I only made it when I was working from home.
83:05And so
83:07I took opportunities when I could, basically.
83:09There were some moments where I could make videos every day.
83:12And there were some other moments where I haven't made a video for three months.
83:15And it's I I just
83:16I'm just at peace with that, right?
83:18Because I have a a matrix where I say, right, the first thing I do every day is my job, nine to five.
83:23Um before that, I'm a father, I'm a husband, I'm a dog walker.
83:27So I do all of those things.
83:29And if I get to the end of the day and it's 7 PM and I don't, you know, want to sit on the sofa with my wife for whatever reason, maybe she's watching something I don't want to watch.
83:38I ask myself, do I feel like making content?
83:41And if I do, I come upstairs, I switch the camera on, and I think, right, what could I record a video about?
83:46And I don't script my videos.
83:48I know a lot of people
83:49um sort of do script their videos.
83:51I don't script my videos because I don't have time to script the video and then record it some other time.
83:58So when I sit down to record a video,
84:00I have to record it there and then.
84:02So I think about it.
84:03I'm like, what am I going to teach people?
84:05And I say, okay, I'm going to teach them this.
84:07And we do it.
84:08And that's it.
84:08And I have to edit it before I get up again.
84:11Because if I don't.
84:13I might not get back to my desk for two, three more days.
84:15That's sort of where I am today.
84:17And so if you look at my channel, it's very irregular, but
84:21At different moments in my life, I've had the opportunity to make more, I've had the opportunity to make less.
84:26Um, I've been ill as well.
84:28I I was very unfortunate two years ago.
84:30I um I had cancer, and that meant I could make content for about three months.
84:35And I had to stop.
84:37I had to really stop to make content because I wanted to make content, but I had to stop and just let myself have time to heal, have time to spend with family.
84:47And so
84:49The best way to do this is to just always promise yourself that you're not gonna kill yourself doing it.
84:55If you're not enjoying it, don't do it
84:57Yeah?
84:57If you don't have time to do it, it's okay.
85:00There is no race.
85:01If you make good content, it will always find the right audience.
85:05You know this, right?
85:07Um people are finding you today and they're finding videos you made two years ago today, right?
85:12Like this has always happened, right?
85:15And this is this is now your problem because people are finding stuff you made two years ago and they're saying, Yeah, what about this?
85:21What about that?
85:22But that's just how it works.
85:23And you have to be at peace with it, let it be
85:27um you're helping people as well.
85:29So you know choose choose choose choose the framework upon which you
85:36You want that to happen.
85:37Yes, people can ask you to do stuff, but you've got to really want to do it.
85:41Because if you make something that you don't want to do, I think your audience can really tell.
85:45Like you can really tell in the content.
85:47And no one will watch it and they'll just go somewhere else because someone else will do that.
85:51So yeah, long answer, but I think yeah, it really starts from sort of the heart.
85:56Yeah.
85:56Understand yourself and give yourself the time.
85:59Exactly.
86:00This is the the correct priorities, you know, health, family, your stable job, and then your hobbies or side projects.
86:08Yeah.
86:08And I and
86:10I think we don't have to compare ourselves.
86:12I cannot go and compare now myself with Tim.
86:15I cannot compare myself with other content creator
86:18Each one of us has different parameters and setup and they have their own life and it depends, yeah, how much time left and how you divide your energy through the day.
86:26For example, I know when exactly my wife is, let's say, ready to watch some TV or we when we're gonna make a dinner.
86:33So I know exactly at the morning I have enough time.
86:36And then later I will not have a time.
86:38And I know in the weekend, for example, the first five hours is uh nothing to do, so it's time to do recording videos.
86:46But if I had kids, if I had like a dog, maybe like I would I would have like different program and different style.
86:54Maybe I'm gonna be producing a video a month, you know?
86:57Yeah, that means exactly I I was looking as well to other content creators making a lot of content and stuff, but I cannot compare myself.
87:05It's it's something that will never work.
87:07We have we have all different lives.
87:09And yeah, at the end.
87:11And even if like my life was busy and I didn't have the time to make content creation, I'm gonna be very grateful to have a job and I'm working as a company and I would never leave it.
87:22So
87:22This is because the parameter changed in my life.
87:26So everyone is enjoying the content and if people are pushing on me, let's say, to make more content and it is working.
87:32That's why I left.
87:33So yeah, there is no predefined path for this.
87:37Each one of us has different parameters and we will make decisions that uh will you would never expect I would never expect to do this
87:45So that's why you cannot plan ahead a lot.
87:47Just plan like the next few months and that that's that's more than enough.
87:51And yeah, health is the most important thing.
87:54So we have to take care of it.
87:55This is the best investment that we can do.
87:58Health in our brain, health of our uh body.
88:00Like I need to have good shape in order to sit behind this disctop and start doing my job.
88:06Now if I have back pain or something like that, I would not be able to work at all.
88:11So
88:11Yeah.
88:12Investing the health is it's the most important thing, I think.
88:15It's so easy to look at content creation and almost become enamored in in the art of creation.
88:21Like I must make a video, I must
88:23And YouTube doesn't help.
88:25YouTube, the way it shows your data, the way it talks to you, is kind of sort of, it's like poking you in the corner, like, go on, go on, go on, you know, all the time.
88:35Um, but you have to again go back to yourself and really try and understand what do I really where do I need to really be right now?
88:43and who needs me the most sometimes you need yourself more than other people need you and you have to you have to listen to that um before you sort of sacrifice yourself almost to um yeah to make content so yeah
88:56Oh my god.
88:57Tim, I can't stay like asking a question and talking to you for I think for forever.
89:03We have a lot of things in common, you know, about content creation, about the work.
89:07I think we can
89:08talk a lot about a lot of topics, but I don't want to let's say uh take a lot of time from you but um we are already one hour and a half maybe let's start them taking some questions from the shots yeah I would say um
89:22It's time for Q<unk>A, I'm gonna say, and you can ask us anything.
89:26I can pick questions or you Tim as well from your I think you are as well streaming at your channel.
89:32I am so I think questions or I can
89:35Yeah.
89:36Um, F1 predictions.
89:38Oh, this is a great question from Paul R21129.
89:43Um
89:44This season's gonna be interesting.
89:46I think the first six races are going to be spent understanding the cars, um, the F1 Formula One cars for everyone who's new to this.
89:54Um
89:56There is a new set of regulations for Formula One.
89:58So the cars work differently to how they've worked for the last three years.
90:02Uh four or five years actually.
90:04And what this means is the drivers have to learn a new way of driving.
90:08And so I think the first um five races, we won't really know who's doing well.
90:15But I will put my hands out and say I think um either Ferrari or Mercedes will be able to do something special this season.
90:24because they have the most history in the sport and they're probably the most experienced at learning new regulations.
90:30Red Bull have a new engine, so they have to learn how to build an engine for the first time.
90:35Aston Martin have a new engine with Honda
90:38Um everyone else is using Mercedes or Ferrari.
90:41Audi is also new, learning a new engine.
90:44So yeah, if you're learning a new engine and learning a new car, it's going to be a hard shift.
90:48So Ferrari and Mercedes are my two two teams to look out for.
90:52Yeah.
90:53Oh nice.
90:54I didn't know that.
90:56Thank you.
90:58Um I'm gonna pick maybe here.
91:00A little bit long question, but whether that engineering is relevant for 2026.
91:05My friend, data engineering now, like I'm gonna speak from my own, you know.
91:09It is gonna it is more relevant than ever.
91:12Before we were just preparing data for data analysts or maybe data scientists and stuff like that, but now data engineers are preparing data for AI use cases.
91:22So um with the AI hype, we are more important than ever.
91:27And without having data engineers implementing the company strategy, data strategy.
91:33We will have uh garbage out of the AI.
91:36That's why uh companies are now building something called data products
91:41And they are extracting as much as they can from data from their systems to feed the AI.
91:47And we are the guys or
91:49Girls are um bringing the data from the sources, making it available for the AI.
91:56And that's why we are now very valuable for the companies, and of course they need data engineers for that.
92:03So this could be my take on that.
92:07Yeah, I totally agree.
92:08Um I think tools around data are about to go through a huge change.
92:13Um, if you think about many of the tools today, they were built in an era where there was no AI, there were there was very few things like APIs, and so
92:24If you build a data product today, you'd build them entirely differently just because the technology landscape is different.
92:30And a lot of people thought of their concepts, you know, the tools that we use today are probably two, four, five years old in terms of technology.
92:38And so, you know, the next three years we're going to see tons of innovation, not necessarily linked to AI, um, but you know, specifically linked around user interfaces.
92:50The way we do our jobs, the way things connect, and that will that will have a meaningful impact on the quality and the breadth of these tools as well.
92:58So uh we're still definitely gonna have jobs.
93:00We're just gonna be doing things very differently.
93:05Nice.
93:06Um let's pick maybe another question.
93:10If you have anything from your site, Tim.
93:12Um yeah.
93:14Yeah, we can
93:15How do I want YouTube content without fear of talking nonsense?
93:19This is an interesting one.
93:21I think um you're maybe asking how do I watch YouTube content without
93:26Uh uh fear of talking nonsense.
93:28So maybe you're saying how do I make YouTube content without the fear of talking nonsense?
93:33Um
93:34If I answer all of those questions, every time I hit record, my biggest fear is I'm talking nonsense.
93:45And you just have to be humble.
93:48You just have to be humble when you get something wrong, correct it, accept it, learn from it, and move on.
93:57People who don't learn from their mistakes are the ones who dwell on their mistakes.
94:02And so the biggest thing you can do if you want to learn is just be brave.
94:06Do your best to be correct.
94:08I will say this: that there is a lot of YouTube content that is teaching what I would sometimes consider incorrect, or sometimes I'd consider out of date.
94:18And they're they're publishing it today like it's today's sort of best.
94:23So if you just do your homework, try and learn the best.
94:27techniques today.
94:28Genuinely research your ideas.
94:30If you don't know them, research them.
94:31If you know them, practice them, showcase them.
94:35And just understand that everyone is afraid when they hit record.
94:41What they are happy with is how they handle mistakes.
94:44And that's the difference.
94:48Like I would I would maybe give a tip for this as well, Tim.
94:53If you want to understand how everyone started YouTube channel, just go to their channels, sort the videos ascending by creation date.
95:02And check the first two videos and look how we talk.
95:05Like you can check my video, my first video.
95:07Each time if I want to laugh, I play this video.
95:11to my wife and we laugh like crazy because I was struggling saying anything and it was one of the I I'm gonna leave the video so I will not hide anything but it was really crabby video.
95:23I
95:24I w I was really uh stressed out and I didn't know what I'm talking about.
95:28So yeah.
95:30We all we all add this phase and we're gonna improve by each video, yeah.
95:35Yeah.
95:36All right.
95:36Yeah, absolutely.
95:37Cool.
95:38Tim, maybe I'm gonna ask you last words.
95:41What gonna be next for Tim?
95:43I know that you
95:45Always try new things.
95:47You are not always like let's say sticking with the same plan.
95:51You have always like I saw you have a lot of YouTube channels as well.
95:55You tried to show some products.
95:58You are as well maybe people don't don't know, yeah.
96:00You showed me a lot of amazing images about constructing PCs and uh towers.
96:06So it's you're gonna always like surprise me, you know.
96:10So I'm really interested to understand the what's gonna be next for Tim.
96:14It's a great question.
96:15Um if I'm if I'm if I'm really being honest, this year um
96:22To answer this question, I have to step back a little bit.
96:25You know, um my k my kids are very young and for the last six years
96:31We have had a baby in the house, right?
96:34So for the first time this year, there is no baby in the house.
96:39So what this means is all my children are walking.
96:42All my children uh can more or less talk.
96:45They can ask me for things.
96:47And what this does to you as a dad is that you you you think about your time completely differently.
96:54And so for the first time, I'm really taking this time to say, wow, I've been a father of a newborn child for the last five years.
97:02I'm now the father of toddlers and children.
97:06And I need to change my relationship with technology, with time, with my wife, with work.
97:12And in order to do all of that, I have to rediscover myself.
97:15And in doing that, that will naturally change the way I make content.
97:19And so the content is the last thing I'm going to solve because I think solving those other problems are the most important thing.
97:25In the meantime, I'll just keep doing what I'm doing.
97:28But I do think by the end of this year, the way I make content, the content I make will be very different.
97:35I can't really promise what it will be because I don't think I know the answers yet.
97:39I'm still working it through.
97:40Um, I made the mistake of sharing direction too early before I'd really figured it out.
97:47And so I've learned from that mistake and I've said, no, no, no.
97:50I will get this right.
97:51We'll we'll we'll figure out all these experiments and we'll land in the place where I can still teach people about data.
97:59And I can do it in a way that, you know, balances life, work, and everything else that needs to happen.
98:04Um, I'm excited about lots of projects, but I need to just get those things done first before I can
98:10you know, share and really put them in the right context.
98:13But yeah.
98:14So that's that's sort of a long answer, but uh
98:18Tim Tim, I can tell you this is my uh I think tip number three.
98:22I say it's don't share your plan with others.
98:25It's not because you you don't want it's not about hiding a secret or something, but
98:31Each time I share my plans with others, uh it doesn't happen because I get this feeling that it's already done
98:38Especially if you are talking to other people like you know to your friends or colleagues, you know, I'm gonna start YouTube channel, I'm gonna make those videos, and uh the second playlist is gonna be about this.
98:48Yeah.
98:48So you have the feeling that it's already done and you and your friend's gonna say it is amazing.
98:53So you're gonna get as well the acknowledgement and feedback that everything is done.
98:57So you're gonna get the feeling I am done with this topic and
99:01If you really do it, then you're gonna feel you are doing it twice because you're already done it in your mind.
99:06So don't speak about your plans.
99:08Yeah.
99:08Special in details.
99:10Try to plan it, do something, and then the end results maybe you can share it with others, but it is very risky to share in details.
99:19Because uh yeah, you're gonna feel that it's already done.
99:22And I can tell you something, Tim, maybe it happens yesterday.
99:26Um, I get contacted from a team in USA, they teach data for kids
99:33Okay.
99:33And they ask me whether I can collaborate with them.
99:36So I have no idea what they mean, but I saw their brochure and they really teach statistics and charts.
99:44For kids.
99:45Amazing.
99:45It's just really amazing.
99:46Maybe I'm gonna share the flyer with you, Tim.
99:48Yeah.
99:49Because they are sharing, like I don't know, yeah, some a par chart, but using some Apple and stuff.
99:56Concepts and
99:57They are trying to teach data visualizations and data concepts as an analyst, I think, for kids.
100:04So I was really interested about it because I think maybe I can help them with the sketches and stuff like that.
100:10So I'm gonna check with them.
100:12Exactly.
100:13And I think teaching data for kids is gonna be something amazing.
100:17Maybe you're gonna do it for your kids and try out another teacher data.
100:23But sketching has so much knowledge, uh, definitely.
100:26There's definitely something there.
100:27Yeah.
100:28But uh, I don't know.
100:29Maybe I'm gonna collaborate with this or we can help them out, you know.
100:33Uh teaching bigger food.
100:35Yeah
100:36It's gonna be this is gonna be interesting.
100:38Yeah, um so Tim, um I believe whatever end up that you are doing, it's gonna be always something that's gonna inspire others.
100:47You inspired me, I own you a lot of uh
100:50Acknowledgement and uh a lot of my where am I now because of you in the content creation rewards.
100:57So thank you so much for that.
100:58Thank you for leaving at my channel and uh pushing me
101:02to keep going and as well thank you for everyone that are listening now to us or liking watching stuff you guys pushed on us to make more content
101:12And uh yeah, I'm really happy about this conversation.
101:15I I could go f way more longer.
101:19Six hours.
101:21Yeah, but maybe we can repeat this again, Tim, when you have a feeling that you have time and you would like to talk to me again, talk to us.
101:29It is really amazing.
101:30I really didn't feel that we are in live stream where we just have
101:33Normal conversation like usual.
101:36Then thank you so much.
101:38Maybe some final words to people are watching
101:41Um yeah, keep keep following Barra, keep pushing him to make great content.
101:46Uh don't let him off.
101:48He's he's on fire.
101:49I saw someone say that you're nearly at 300,000 subscribers if you're watching this and you're not subscribed.
101:55Hit the subscribe button.
101:57Barrow deserves it.
101:58Don't let go.
102:00And um, yeah, it's honestly been a pleasure to be here um to talk to your audience, to talk to you.
102:05We talk behind the scenes, but this is different.
102:08I really like to be able to share this conversation with other people.
102:11Um so thank you for having me.
102:12And yeah, um, we'll do this again soon.
102:15You are very welcome, Tim.
102:16Thank you for everything.
102:17And for everyone that are listening, thank you for joining us in this conversation.
102:21I hope that helps one of you or get you inspired.
102:25So keep pushing as Tim said.
102:27And yeah.
102:29We see you in the next stream.
102:30Thank you so much.
102:31Bye-bye.
102:32Take care.
A career conversation between two data content creators on how they got into data, how they learn a client's business, and why the Tableau-vs-Power-BI debate matters less than building durable domain expertise.
- Content inspires, but don't copy it 2:29
Barra describes being inspired by Tim's storytelling-driven videos and applying the same principle to his own content rather than imitating it directly. Take inspiration, then add your own flavour rather than competing for the same audience.
- Both drifted into data by accident 16:21
Tim moved from psychology into Tableau consulting through a chance meeting; Barra fell into data engineering via a student project he didn't fully understand at the time. Neither planned their specialism, which they offer as reassurance that no clear path is required.
- Be the bridge, not the job title 23:26
Clients want someone who can translate a vague business concept into a working solution, regardless of whether that person is labelled analyst or engineer. Staying flexible across that boundary matters more than defending a title.
- Learn a domain by living the process 26:57
When starting a project, first understand the client's working culture and which level of the business you're entering, rather than diving straight into the data. Take a 'horizontal cut' through the whole process, then go deep into each vertical step, observing work directly (a factory floor, a shop) rather than only reading documentation or data models.
- Tool debates are usually Desktop vs Desktop 44:57
Most Tableau-vs-Power BI comparisons only cover the desktop authoring tools, not the full ecosystems; Power BI's Microsoft integration versus Tableau's more open infrastructure explains most of the real difference. In practice the tool is chosen by licensing, scale and existing contracts, not personal preference, so it's not worth over-investing in the argument.
- Mixing tools in one company is normal 50:53
A large organisation might run Power BI broadly for cost reasons while keeping a small Tableau deployment for advanced visualisations that are more fiddly elsewhere. Once you know one BI tool well, picking up another is comparatively quick.
- Expertise compounds slowly, daily 54:16
Deep platform knowledge builds through years of incremental exposure to new problems, not short bursts of study or a certification. Be realistic about the time required and keep going, since most people who 'made it' simply didn't give up.
- AI changes the tools, not the skill 1:08:50
AI can speed up prototyping and review and aid learning, but can't replace understanding the business problem, and many companies are still far from AI-ready due to old systems. The constant across tool shifts is the same: learn the underlying problem-solving approach, then apply it to whatever platform comes next.
- Treat tool comparisons sceptically when they only show desktop products โ enterprise deployment, licensing and governance differ far more than authoring experience.
- Tool choice is usually driven by infrastructure and existing contracts, not personal preference.
- AI hype can promise more than it delivers โ it still can't replace genuinely understanding a business domain.
- Junior candidates face a higher bar now due to AI and a tougher job market.
Reach for this mindset starting on a new client or domain when tempted to just read the data dictionary, or when pulled into a tool-choice debate that's really a licensing decision in disguise.
How this Rollup was made provenance & method โธ
A Rollup is drafted by AI from the video's transcript, then reviewed and edited by Tim. Everything used to produce this one is listed below (the model, the exact prompt, and the source video), so the process is transparent and reproducible.
- Transcription
- On-device: NVIDIA Parakeet v3 for recent videos, OpenAI Whisper large-v3 for earlier ones. The transcript never leaves the machine or gets published.
- Drafting
- Claude Sonnet 5 in the cloud, from that transcript.
- Prompt
- The exact Rollup prompt (v3) โ, the full system prompt, unedited.
- Source video
- Watch on YouTube โ
- Drafted
- 10 October 2026 at 23:38
- Reviewed & edited
- 10 October 2026 at 23:40 ยท by Tim Ngwena
Model + prompt + video is everything you'd need to recreate a Rollup like this yourself. The one thing we don't share is the transcript.
Rights. The video and its transcript are the property of TN Media Ltd. Unauthorised use or download is prohibited. © TN Media Ltd.


