Behind the scenes Receiving the Golden Hoodie | Dreamforce 23

0:00Hey it's Tim here, in this video I actually

0:02take the segment from the keynote where I

0:05got my golden

0:06hoodie, this hoodie that I'm wearing here

0:08inverted and I've just put it out here

0:09because in the

0:10actual breakdown of the keynote I did a

0:13slightly more detailed sort of explanation

0:16of some of the

0:17questions I was asked during the keynote

0:19itself. So I've taken that out and I've

0:21also added some

0:21behind the scenes footage of what it was

0:23like inside of the actual conference venue

0:26because

0:26the public stream was very different to

0:28actually being there so big thanks to April

0:30for sending me

0:31some footage from inside of the actual

0:33venue itself so you can get a chance to see

0:35what

0:36that's like. It's a very short video thanks

0:38for watching as ever let's get started.

0:41But I am so excited because today we have a

0:44very special guest tuning in live from his

0:48home in the

0:49UK, Tableau visionary Tim Nguyen. Oh god,

0:54also known as Tableau Tim. He is...

0:57Hi there fam. You almost need no

1:02introduction.

1:08I wanted to stop it here because this is

1:09the inception moment where I'm in the

1:11keynote

1:12whilst doing a reaction video. I still

1:14laugh at this because it's absolutely crazy

1:16honestly.

1:17So at this point I'm not going to kind of

1:19continue watching myself in this keynote.

1:24The context here

1:25is that initially it's sort of funny I

1:27should have known what was coming but

1:30initially I actually

1:31didn't put two or two together until the

1:33event. But I'd started talking to Tableau I

1:37think two,

1:37two, three months ago actually about doing

1:40something in Dreamforce.

1:42And I just thought, hey, as they have done

1:44with customers, they wanted me to talk

1:47about

1:47AI and how it could help data on this,

1:49specifically around skills and education.

1:51And actually this is

1:52what we go on talking about. And I'll talk

1:54a bit more about my response to the

1:55questions I get

1:56asked here. But anyway, it kind of ended

1:59with a surprise. And yeah, it's been a

2:01pretty incredible

2:02response, frankly, from the community. I'm

2:06absolutely hugely grateful and genuinely

2:09shocked

2:09at the time. And I think afterwards it's

2:12sort of weird. The life of a creator is

2:15completely weird

2:16because I signed my room here in a virtual

2:20event. I'm actually in the keynote, we're

2:24live. Nothing

2:25was pre-recorded. There was incredible

2:27amounts of lag and so a bit of inside

2:29baseball. As soon as I

2:31responded the first time to Larissa, I

2:33immediately knew how much lag there was

2:36because I could hear

2:37the feedback from the, what do you call it,

2:40from the audience, from the room through

2:43her microphone.

2:44So as soon as I said the first thing and

2:47then it came back to me two seconds, I was

2:49like, oh crap,

2:50I need to listen to what Larissa is saying.

2:52And as soon as I think she's about to

2:54finish, start

2:54talking immediately. So the lag is like

2:56hard almost. And that's essentially what I

2:58did for the

2:59whole thing. So every time I responded, I

3:01was actually trying to do that just to cut

3:03the lag.

3:03These are the kind of things that go

3:06through my head here. Rather than worrying

3:08or stressing about

3:09what I'm going to say, that's sort of what

3:11was going through my mind. I was kind of

3:13stressing

3:14a whole ton. I actually start sweating in

3:16this video. It's so embarrassing. I'm

3:18calling it out

3:18now because I can and it's afterwards. But

3:21nonetheless, yeah, I really enjoyed this

3:23sort

3:23of whole interview. Anyway, I'm going to

3:25wait and maybe give a little bit more color

3:27to each

3:28of my responses in this because I think in

3:30this section, I have to give short, sharp

3:32responses.

3:33I did know what questions she was going to

3:34ask me. I didn't know what was coming at

3:36the end. But

3:36I wanted to give more context here because

3:39I think it's important and it's actually,

3:40you know, I sat here and critiqued the

3:42whole entire keynote. I guess I have to

3:44critique

3:45myself. So let's take this a little bit

3:48further. I might skip a few.

3:49Also known as Tablo Tim, he is an analytic

3:52consultant and instructor.

3:54Let's skip ahead a little bit here.

3:55And a YouTube sensation with more than 55,

3:56000 subscribers and more than 2.8 million

3:59views.

3:59Let's double through this.

4:00Yeah. With all of his effort, he is helping

4:03people everywhere for other data sales.

4:04Okay. Let's carry on from here.

4:05Thank you so much for joining us today.

4:06Absolutely a pleasure.

4:10So there you go. That's when I noticed lag.

4:12Okay. How did you get from your very first

4:16viz to where you are now in your career?

4:19So it started out in student analytics. I

4:23was looking at student data at the

4:25University of

4:25York where I studied and I ended up going

4:28to another opportunity to work in marketing

4:31and communications. And the data there just

4:33sort of pulled me in. The problem I had

4:37though is that

4:37the stories that were coming from that data

4:39weren't as compelling. A lot of the social

4:42media data. So another thing I'm actually

4:44quite impressed by is we're using Zoom here

4:46.

4:46Like I'm patched into conference by Zoom

4:50and Zoom held up like it was solid. The

4:52sound was good.

4:53The video quality was coming through

4:54totally fine. I think Zoom compresses the

4:56video down to 720p.

4:58I had like a proper camera going, which

5:00could have pushed a 4k stream to this,

5:02but I think some ACP would have been fine

5:04anyway.

5:04The kind of thing I'm interested as this is

5:08this actually works pretty well. And I

5:09think it's a

5:10good example of, hey, if you can't get

5:12someone to the keynote, if they've got the

5:14setup, you can do

5:15a virtual setup. And that was always sort

5:17of my pitch to tablet. Hey, I can't be

5:18there in person,

5:19but I think I've got a good enough setup to

5:21do this this way. And I think it worked out

5:23.

5:23But anyway, really, really cool. Now the

5:25context of this answer is about how I

5:28actually started

5:28out in analytics. In essence, I used Table

5:31au for the first time without realizing it.

5:33I was

5:34understanding data about postgraduate

5:36students because I worked briefly as a

5:39student union

5:40president, essentially student politics

5:42here in the UK. And the super interesting

5:45thing there was

5:45that the university I went to, University

5:47of York, was one of the early adopters of

5:49Tableau. They

5:49were using Tableau to visualize student

5:51metrics, and they were sharing it on their

5:53website through

5:54like an embedded sort of setup so you could

5:57have this little Tableau dashboard that

5:59people could

5:59explore and you could actually download

6:01your data from it and do various things.

6:03This is very early

6:04days of Tableau. And so I actually did that

6:06. I downloaded the data off a chart and then

6:09repivoted it and did some stuff in Excel to

6:11then go and try and visualize and

6:13understand what was

6:13going on with postgraduate students. Anyway

6:15, I didn't know it at the time, but that was

6:17Tableau.

6:18That was basically what I was using. And it

6:19's only a few years later where I then came

6:22across Tableau

6:23again, like two, three years later, came

6:25across Tableau. This time as like a

6:26professional. And I

6:27realized, hey, I've used this before. I

6:29used it when I was looking at student

6:30politics, but now

6:31I'm using the authoring experience. And so

6:33that's actually sort of how it started. And

6:36I got to that

6:37experience through someone I met at

6:38university, the information lab, so Craig

6:41Bloodworth. And he

6:42encouraged me to say, hey, come join this

6:44small company. It's called the information

6:45lab. You'll

6:47learn a lot more about data than working in

6:49marketing and communications. So that's

6:50what

6:50I did. I joined back then when it was a

6:53company with 11 people. And then fast

6:55forward a decade

6:56later, information lab has grown. I've

6:58since moved on from the information lab. I

7:00've worked

7:01at Accenture and now work at Endpoint

7:03Digital. And it's super interesting just to

7:06see that journey.

7:07And I think I'd go on to explain more about

7:10that. But in essence, it started off with

7:12sort of my

7:14passion for quantified self, which is what

7:15really sort of made things connect in my

7:17mind. It made me

7:18really understand that I was getting

7:20passionate about data, my own data in a

7:21specific way. And

7:22actually businesses had the same passion

7:25with their own data. People in businesses

7:27really

7:28understood their businesses as well as I

7:29understood my music data, as well as I

7:31understood my running

7:32data. And so in talking to people and

7:34talking to people about their data, I

7:37started to see

7:38some challenges, things that weren't quite

7:39clicking, concepts that weren't working in

7:41Tableau. And so what I did way back when,

7:43if you go to the oldest videos on this

7:45channel,

7:46you'll see the first one's about layout

7:47containers. You'll see some others about

7:49Tableau 10 and design. I just thought, hey,

7:51let me make some videos just highlighting

7:53these things

7:54so that I can point people to them and see

7:56what they're like. I started and I stopped

7:59and I gave

7:59up basically. I did it for like three

8:01months and then I gave up. I just did the

8:03classic sort of

8:04defeated setup. And what was super

8:06interesting about that is that having done

8:08that,

8:09we then, you know, I just sort of carried

8:12on for another two years, went to Accenture

8:16.

8:16And at Accenture, I came across this

8:17problem again, but this time it was with

8:19younger day

8:20trends, people who were just starting out

8:22as associates at Accenture and they were

8:24just starting

8:25a career and asking me, hey, how do I use

8:26Tableau? How do I do this? How do I do this

8:28?

8:28And it was really easy to explain to them

8:30what was going on, but I just ended up most

8:32of the time

8:33just getting on a call and just showing

8:35them. So I thought, huh, what if I just

8:37record videos

8:38instead and then send them the link? That

8:39would be much faster. So that's what I

8:41started doing.

8:42And then I gave up again. And then right

8:45before COVID, there was an opportunity that

8:48came up to

8:49go to New York for a reason I won't go into

8:51. And it didn't play through because

8:54something happened

8:55in my life that changed sort of the outcome

8:56of that. So instead of going to New York,

8:58I ended up staying here in the UK. And

8:59after that, I was like really bummed out

9:03that I wasn't going

9:03to New York. So I thought, you know what,

9:05God damn it. Honestly, seriously, what can

9:08I do?

9:08Is there a way I can do what I was going to

9:11do in New York without, you know, without

9:14sort of

9:14changing something? Could I approach this

9:16concept in a bigger way? Can I make a

9:17bigger impact

9:18doing something else? I look back on my

9:20videos and I thought, you know what,

9:22actually I can.

9:23I can go back to that concept of videos and

9:25start making more. So I pledged to make

9:27three videos.

9:28I pledged to make a video explaining what

9:30Tableau is. And I pledged to start making

9:32videos about

9:32what's new in Tableau. So the new in Table

9:34au videos are what came first. Four months

9:36later,

9:37you saw the What Is Tableau video that was

9:39basically planned like before that video

9:42was

9:42released. Well before. And yeah, here we

9:45are. What at 55,000 subs later, and you

9:49know, many more

9:50thousands watching every single week, every

9:53month. We're hitting milestones. And that's

9:56supported lots of people on LinkedIn,

9:58essentially taking the same concept, just

10:00scaling it up and

10:01explaining to people what Tableau is and

10:03helping people understand how to use it and

10:05how to work

10:06with data fundamentals. And so that's what

10:08this conversation was actually sort of crun

10:10ched down

10:11from. That was sort of the full context,

10:13but it was synthesized just to fit in this

10:15sort of three

10:15minute segment in the key. So I thought

10:17that was useful context nonetheless. And

10:20that's sort of

10:20what we spoke about. And I'm not sure I'm

10:22now willing to live it to myself, go

10:24through any of

10:25that in like a third of the time, but

10:27nonetheless, yeah, that's what it is. So

10:30let's quickly, I might

10:32double speed through this and just go right

10:34past the end. So let's watch this quickly.

10:36- To the time just measured the likes and

10:38these sort of basic metrics. And so I ended

10:40up finding

10:41a route into analytics. And when I started

10:42to work with data, I started to realize the

10:43business was

10:44super passionate about their data. But the

10:45moment it clicked was when I started

10:46looking at quantified

10:46self data. That's the kind of data Ryan was

10:48talking about, data from Strava, Last of M,

10:49and so on and so forth. And it's only then

10:50I realized that the passion I had for my

10:51own data

10:52was the passion that businesses had for

10:53their data. And so I started to spot some

10:55common themes

10:56that people were struggling with as they

10:58were working with their data. And I thought

10:59I'd start

11:00to make a visual way of sort of helping

11:02them understand those problems and get past

11:04them.

11:05So that's how it started. And then here we

11:06are today.

11:07- Such a story journey. Now, many people

11:11here are-

11:12- I think Larissa also understood the lag

11:14was quite big because she cut in

11:16faster than I think it would have taken for

11:18that. So I think we were both doing this

11:20thing where

11:20she knew what I was going to say, generally

11:23speaking. So she knew when I was coming to

11:25the

11:26end of my point. So she could just actually

11:28cut in and I could do the same as well

11:30because I kind

11:30of knew the general question she was going

11:32to ask me. So we kind of did some great

11:35teamwork here to

11:35kind of make it work with less lag than the

11:38Atlanta Ocean actually allowed. So that's

11:40pretty funny.

11:41- So just getting started on their

11:43analytics journey. And it's a little bit of

11:47a different

11:47landscape today. What has you most excited

11:50as you think about Tableau and this new AI

11:52revolution?

11:53- I think AI has this incredible

11:56opportunity to amplify people who are

12:00already exceptionally

12:02skilled, sort of raise their skills up to

12:04the ceiling. But also for people who are

12:07struggling

12:07to get into these topics or struggling to

12:09pick up these skills, it actually has an

12:11ability to

12:11lower the barriers, almost help them get

12:14into these topics. And so it can simplify

12:17the entry

12:17points for a particular topic. We saw

12:19Hunter do a nice demo there. But also I

12:21think it's got this

12:22ability to help people with their skills.

12:24It kind of brings them into a topic so they

12:26can understand

12:27what to Google. - So what's going through

12:29our mind right now is like, this is just

12:31stressful.

12:32I make videos all the time and it's no

12:35different to the videos except for this is

12:39live, right? And

12:40I'm not going to a script either. I'm not

12:42reading like a teleprompter. I actually

12:45thought after the

12:45event, why didn't I just set this up as a

12:47teleprompter? I wouldn't have been

12:48stressing

12:49myself out trying to make sure I thread the

12:51point I was trying to make in less sort of

12:54compressed

12:54time, rather than just waffle on like I do

12:56here and like I do in most videos actually.

12:58And so you can see on my face, I'm

12:59literally stressing. If you see like sort

13:02of the

13:02sort of silver lining, it's so bad. It's

13:06honestly embarrassing, but the room wasn't

13:10even that hot.

13:10It's just one of these things where you're

13:12panicking because that's just like how the

13:15human body works, right? And I just

13:17suddenly got really, really hot. And then

13:20yeah, I just

13:21started panicking, I guess. Started

13:23sweating my head off. - And then how to

13:25build on those skills.

13:26- Now with your platform, you're bringing

13:29data skills to so many people.

13:31What is something that you can share with

13:33us about teaching and giving back?

13:35- It's a super interesting... - That meme

13:39of the guy sweating previously comes to my

13:42face at the

13:42moment. - I think one of the things that I

13:46always tell people is that when I make

13:48videos, I learn a

13:49lot more about the topic than I would have

13:51done if I just went to learn about the

13:53topic. So teaching

13:54kind of makes you understand the topic to

13:56another level. And when you put that

13:57content out there

13:58into the community, you get sort of

14:00responses. People ask you more questions.

14:01And actually those

14:02questions are the best questions to answer

14:04because they enhance your understanding. So

14:06it's this sort

14:06of nice feedback loop that just sort of

14:09happens. And what is nice about that is

14:11that I got my sort

14:13of breaking data through the data farm and

14:14it's just been really special to sort of

14:16give it back

14:17as well. So hopefully that cycle continues

14:19and we keep building the data farm. - Well,

14:21speaking of

14:22giving back, you've done... - At this point

14:24, I am just absolutely... The sweat is fully

14:27formed.

14:28I think if you'd gone on for another two

14:30minutes, you would have seen one drip down

14:31my head,

14:32honestly. I don't know why I'm tearing

14:33myself apart here, but it's just so funny.

14:35I don't know.

14:37If you've ever been on stage in front of

14:38people and had this feeling, you know

14:40exactly what I'm

14:40talking about. But anyway, here we go. - So

14:43much for Tableau and for the data farm.

14:46Before I let

14:47you go, I have one more thing I'd like to

14:50share. It's a golden honey and we have one

14:53in the mail

14:54on its way to you now. Tim, you truly

14:57embody what it means to be a Tableau

15:01community leader

15:02and a visionary. Thank you so much for

15:05everything that you've done.

15:08Congratulations again and thank

15:10you so much for joining us today. Let's

15:11give them a round of applause. - Thank you.

15:19-

15:20Wow, what a magical moment. I wish you

15:22would have been here, but this was fun too.

15:24Back in 2023...

15:27[Music]

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