2022 Tableau Conference Keynote in 20 minutes - #data22

0:00Hey, I've just finished watching the

0:01keynote for a second time. I'm going to try

0:03and round it up in

0:04under 20 minutes. This is your keynote

0:06roundup. Let's get stuck in. Now I've got

0:08timestamps below.

0:09So if you want to jump ahead straight to a

0:11new feature, those are all marked in the

0:13timestamp

0:13below. So you can check those out. But I'll

0:15start off with a high level overview of

0:17what the keynote

0:18was like. The keynote was essentially two

0:20things. It was the main keynote we're used

0:22to and devs on

0:23stage in one session. Typically, we're used

0:25to having these two separately. But

0:27actually,

0:27if you go way back when to previous

0:29conferences, there used to be one event.

0:32Now this could be for

0:32a couple of reasons. It could be that it's

0:34only been a few months since the last

0:35keynote just a

0:36few months ago, because the conference was

0:38pushed forward to May. And therefore we've

0:40had a little

0:41less time for some of these features to

0:42bake in the oven. But nonetheless, that was

0:44sort of the

0:45overall high level split of the conference.

0:47Now in the first half, we had Mark Nelson

0:48essentially

0:49leading the charge opening the keynote,

0:51along with Andy Cottgrieve, who kind of

0:53warmed up the crowd

0:54and got the energy levels going. But then

0:57we had three customers who essentially came

0:59on to support

1:00some of the core messages and sprinkled

1:03into that we had some features announced,

1:05we had the

1:06rebranding of Tableau online to Tableau

1:08Cloud. And then we also had some

1:10capabilities around data

1:11storytelling that were revealed a little

1:14bit more. After that, the main gist of the

1:16features was

1:17essentially developed through the devs on

1:19stage section. And in there, we got a whole

1:21sort of

1:22quickfire round of features that I'm going

1:23to go through now in a little bit more

1:25detail.

1:25But let's actually start from the top. Let

1:27's start with the very beginning of the

1:29keynote. Now,

1:29if we start from the top, Mark Nelson

1:31essentially started by talking of a concept

1:33called the data

1:34gap. Essentially this problem where data

1:37leaders want the data skills of their

1:40employees to be

1:41much further along than they actually are.

1:43And essentially how Tableau can help bridge

1:46that gap

1:46by making analytics available to basically

1:49everywhere for everyone. That was the exact

1:52phrase he used. And then he sort of moved

1:55on to drawing parallels to how this vision

1:58is sort of

1:59shared by Salesforce. It was a very sort of

2:01smooth operator way of getting people into

2:03a pitch about

2:05how Salesforce and Tableau have a sense of

2:07shared values. And he essentially used four

2:09key points to

2:09highlight that. The first one was community

2:12, touching on the fact that Tableau has a 1

2:15million

2:16strong community and Salesforce has a 16

2:18million strong trailblazer community. It's

2:21kind of

2:21interesting because he talked about them as

2:23if they were separate products, but

2:25actually they

2:26are separate products, but they're now part

2:28of the same company. And that was sort of

2:30the thing that

2:30was interesting. He kind of didn't go as

2:32far as to say, "Hey, we're all part of the

2:34same family now."

2:35But that was sort of implied by the way the

2:37conference was set up, the stage, the

2:39characters,

2:40everything about this felt very Salesforce.

2:42So that was sort of implied. And the next

2:44point was

2:44technologies, talking about the excellence

2:47in technology that both companies have had

2:49in the

2:49past, Salesforce in the CRM world and Table

2:52au in the analytics space. And the idea that

2:54by

2:55bringing these two things together, you

2:57essentially have the opportunity to unlock

2:59a whole world of

3:00data because Tableau is an analytics

3:01platform, allow you to go and connect lots

3:03of disparate

3:04data sources together and get insights from

3:06them. And Salesforce on the other hand has

3:08done a good

3:08job of building a world-class customer-

3:11focused CRM platform, but there's a lot of

3:14unearth data

3:15that's not being used in there. And of

3:17course, these two together will help sort

3:19of open up

3:19that world to more people. And that's sort

3:22of the general idea that he was trying to

3:24push there.

3:24The next thing was on values. And

3:26essentially here, he talked about the idea

3:28that Salesforce

3:30and Tableau have actually had a sense of

3:32shared values when it comes to making sure

3:35that people

3:35have access to data, whether it's two

3:37things like the Tableau Foundation or the

3:39Salesforce

3:40grants that Salesforce have been doing all

3:42along. And actually these two things are

3:43sort of very

3:44similar initiatives in real terms. And Mark

3:46was drawing these concepts together to make

3:48it really

3:49abundantly clear. There's actually a lot

3:51more to both companies than maybe the Table

3:53au community

3:54is sort of familiar with. And the last one

3:56was product potential. The idea that if you

3:57bring

3:58these two behemoths of their respective

4:00spaces together, there's so much more

4:02potential available.

4:03He used the idea of peanut butter and

4:05chocolate. I actually don't think that's a

4:07great combination,

4:07in my opinion, but nonetheless, he said it

4:10would be even better if you put those two

4:11things together.

4:12And so that was essentially, I think, a

4:14very strong Salesforce page. I think there

4:16is a

4:17good amount of sentiment in the Tableau

4:19community at the moment that Salesforce

4:22branding and

4:23marketing is being sort of pushed into the

4:26Tableau world without much value coming

4:30from

4:30the Salesforce world to show us what Sales

4:32force can offer Tableau. And it goes vice

4:34versa as well.

4:35We'll maybe do a separate video on that.

4:36But nonetheless, that was sort of the key

4:38message.

4:38Hey, look, Salesforce and Tableau, two very

4:41similar companies, two very similar ethos,

4:43two very similar cultures coming together

4:45to create something amazing. That was sort

4:47of the

4:47key message. We then moved on to the next

4:49phase of the keynote, which was essentially

4:51looking at

4:52three separate customers. Now I'll start at

4:54the top by showing you who these customers

4:55are.

4:56It was JetBlue, Standard Chartered and Feed

4:58America. These were the three organizations

5:00and actually three very different

5:02organizations to have on stage, all telling

5:04their own stories

5:05about how Tableau has enabled them to go

5:07forward. Let's start first with JetBlue.

5:10JetBlue was,

5:11in a way, a really good example for Tableau

5:13to showcase something they believe in,

5:15which is

5:15the power of the cloud. And in this

5:17particular section, JetBlue was here to

5:19talk about this

5:20concept of moving faster with analytics

5:23technology. And the key driving part of

5:26Tableau that enables

5:27you to do this is Tableau Online. The idea

5:28that you can take a product and essentially

5:30,

5:30without much sort of setup work, you can

5:33have an infrastructure built out available

5:35through

5:35your organization done very, very quickly

5:37and in a very agile way. Now, this was then

5:40used to help

5:41rebrand Tableau Online to the Tableau cloud

5:44. Now that's a very small change, but I

5:47think it's an

5:47important one to try and get people

5:49familiar with the difference between Table

5:51au Server, which is the

5:52on-premise offering, and Tableau Cloud,

5:54which is what I'm going to call it now,

5:56which is the cloud

5:57offering from Tableau with a fully managed

5:59solution that then also enables a bunch of

6:01other

6:01technologies to come and follow on from it.

6:04This then broke off into a little bit of a

6:06feature

6:07sort of run through. So the great thing

6:09about this with now Tableau Cloud being

6:10sort of showcased,

6:11they showcase this amazing opportunity to

6:14have region-specific sites for Tableau

6:17Cloud. I keep

6:18trying to say Tableau Online, but

6:19nonetheless, region-specific sites for

6:21Tableau Cloud. That's

6:22two features. First of all, you can create

6:24sites for each and every Tableau Cloud

6:26instance. And

6:27then secondly, you can make them region-

6:29specific, maybe necessarily for compliance,

6:32but also for

6:32performance. Let's just imagine you're an

6:34organization who's spread across multiple

6:36parts of the world. You might have

6:38compliance or geographical restrictions

6:40that mean you have

6:41to have different Tableau servers in

6:43different locations. And through Tableau

6:45Online and managed

6:45sites, you can essentially have this

6:47capability out of the box. This is a really

6:49big feature,

6:50and it's something that a lot of people ask

6:51for. I can see the Tableau Server fans out

6:53there

6:54starting to look at this with lots of envy.

6:56We're not clear if this will come to Table

6:58au Server at

6:59all. I doubt it will because this is again

7:01being done by Tableau, but it would be good

7:03to see the

7:04technology doing this come out in some way

7:06or form where Tableau Server admins can

7:08sort of enable this

7:09and work with it, even if it means working

7:12with AWS or Microsoft Azure in order to do

7:15that.

7:15We then got a few small things, things like

7:18customer-managed encryption keys for

7:20extract.

7:21And then also we got a hint of what seems

7:23to be another add-on, but I think this is

7:25actually just

7:26a rebranding of an existing add-on. I'm not

7:28entirely sure on this, so don't quote me on

7:30this,

7:30but I think the Server Management add-on is

7:33just being rebranded to the Advanced

7:34Management add-on

7:36so that it can too serve Tableau Online,

7:39now Tableau Cloud, as well as Tableau

7:41Server. I

7:41think that's what's going on here. And so

7:43some of this stuff will come through that

7:45capability for

7:46customers who really want sort of the full

7:48capability of Tableau. They'll need to get

7:50this

7:50server add-on in order to get these

7:52features specifically on Tableau Cloud. The

7:55other small

7:55thing was Admin Insights, essentially

7:57getting a little bit of an improvement. Now

7:59, Admin Insights

8:00for Tableau Online, now Tableau Cloud, have

8:02actually been around for a little while,

8:03but

8:04they didn't come on by default and they're

8:06quite basic. Now I think what's going to

8:08happen is you're

8:09going to get slightly better sets of data,

8:12maybe even longer periods of time for the

8:14amount of

8:15history that those data sources have, but

8:18also access to more data sources and pre-

8:20built workbooks

8:21as well that you can use alongside your

8:23Tableau Online instance. And then that was

8:25sort of the end

8:26of the JetBlue segment. That was sort of

8:27the end of this whole section. They were

8:29essentially using

8:30customers to showcase specific features,

8:32which was, I think, a nice touch because it

8:34drew parallels

8:34to these companies. Now this then creates a

8:36new problem because the next customer didn

8:39't really

8:39have any product feature behind it. And I

8:41think this is why maybe this particular

8:43customer stood

8:44out as not being very convincing when it

8:46came to the keynote. I'm not saying

8:48anything whatsoever

8:49about the actual content of the keynote

8:51here. All I'm just saying is that it was

8:53very hard to draw

8:55any sort of learning from the keynote to

8:57understand why that customer, what that

8:59customer has done

9:00that's different from many other

9:02organizations to make them a standout

9:04example in the keynote.

9:06And so the example was standard chartered

9:07bank. And essentially here we're talking

9:09about a data

9:10culture and the idea that you can use the

9:12opportunity of training people up with data

9:15to make your workforce happier, stick

9:18around more often, but more importantly,

9:20enable a data culture.

9:21And essentially the individual that was

9:23just on stage talking about this just

9:25basically talked

9:26about how Tableau has helped them do this

9:27and how they've created a center of

9:29excellence,

9:29essentially around this philosophy to help

9:32galvanize its culture and community to go

9:34from

9:34a 400 strong server all the way up to 10,

9:37000 in a very, very short amount of time. A

9:40story that's

9:40played out actually in quite a few

9:42organizations, but it's very, very hard to

9:44replicate. And

9:46something called the Tableau blueprint is

9:47sort of designed to help you figure this

9:49out. But nonetheless

9:51this was just an example of a customer

9:52talking about how that has helped them go

9:54forward.

9:55We didn't have enough tangible examples or

9:57features to really sit behind this either.

10:00And we didn't have anything new. Maybe

10:01something got pulled from the keynote for

10:03this particular

10:03customer. Who knows? After standard chart

10:05ered, we had a sort of a change of energy.

10:07It was sort

10:08of the halfway mark and Francois, the chief

10:10product officer came on stage and actually

10:12just stepped

10:13out of the keynote a little bit and

10:14reminded us all about the nostalgia, about

10:16how Tableau became

10:18the product that it is. It was this sort of

10:20a small innovative product that came out of

10:22the

10:23basement of analytics and brought analytics

10:25to the stage as he said. And what was

10:27really good about

10:28this is that I think this keynote really

10:31needed this at this time. We just had a

10:33very, let's just

10:34say we just had a lot more content sort of

10:37pitching us on the philosophy of various

10:39aspects of Tableau,

10:40things that we've heard before. And apart

10:43from the Tableau Online to Tableau Cloud re

10:45brand and the

10:46feature set there, there wasn't really much

10:47in the keynote at this point. So Francois

10:49came on stage,

10:50reminded us all about why we love Tableau,

10:52why the community has come, and then

10:55started to pin this

10:55to a customer story that also landed really

10:57, really well. The Feed America story was

10:59actually

11:00really powerful. It's not a very

11:01complicated one. It's not a sophisticated

11:03story. It's just a simple

11:04story about how a company or organization,

11:07and not for profit in this case, has a

11:09mission to help

11:10make sure that people have access to food

11:12and that they use data to help solve that

11:14problem.

11:15It's a story that gets played out many,

11:17many times. Except for here, they were

11:19drawing parallels to

11:20the impact it has on people, communities,

11:22and how Tableau has enabled their

11:24organizations and their

11:26partners through collaborations with people

11:28like the Tableau Foundation to push that

11:30philosophy

11:31forward. And so that was a really, really

11:33good customer story. It landed really well

11:35with me.

11:35Maybe it's just me. Let me know what you

11:37think in the comments. But nonetheless,

11:39this drew a really,

11:39really nice thread because Francois then

11:41came on stage and said, "Well, this is

11:43great. We have

11:44people using data to tell the story, but

11:46there's even more people in every business

11:48that can't

11:49work at the level that authors like myself

11:51work at." In essence, not everyone is data-

11:55driven,

11:56to borrow the phrase. Not everyone is

11:58excited by data. So how can we help the

12:00people who

12:00can't build these stories easily, aren't

12:02familiar with these, or maybe don't have

12:04the data literacy

12:05but shouldn't be excluded from the

12:06narrative? And that's where a new feature

12:08was introduced

12:09called Data Stories. Now, Data Stories is a

12:12really interesting announcement because it

12:14's essentially

12:15the product that's come out of an

12:16acquisition, a previous acquisition from

12:18Tableau around a

12:20thing they're commonly called narrative

12:21science. If that's wrong, let me know in

12:23the comments.

12:24But essentially, this technology looks at

12:26your workbook and essentially builds a

12:28story just

12:29purely using text. And this works like an

12:31extension. The interesting thing is a lot

12:33of

12:33the features today are actually extensions

12:35of Tableau. They'll be in the Tableau

12:37economy in

12:37the extension gallery. But nonetheless, it

12:39was an interesting feature because Tableau

12:41pitching this

12:42as a way to bridge that gap, as Mark set

12:44out to talk about at the very beginning.

12:46How do you get

12:47those people who might never build

12:48something but need to know what's going on

12:51in a dashboard,

12:52and maybe just can't pull out the insights?

12:53People who can't necessarily browse or

12:56engage with an

12:57analytical dashboard or anything like that,

12:59don't even know where to start. This was

13:01giving a

13:01narrative sort of story alongside the

13:04visualization. And out of the gate, it's

13:06got a pretty strong

13:07feature set. It works on mobile, it

13:09actually supports accessibility guidelines

13:11as well,

13:11not just because it's built with

13:13accessibility in mind, allowing you to

13:15customize how it works and

13:16how it looks. But also, if you think about

13:18it, for people with visual impairment, it's

13:20actually going

13:20to be a really nice add on because it's

13:21just a browser extension. Essentially

13:23inside of the

13:24dashboard, screen readers should be able to

13:26read the text from it as well, making dash

13:28boards a

13:29little bit easier to understand. And I

13:31think that might become the primary mode

13:33for people who are

13:34visually impaired to listen and understand

13:36what's going on inside of a dashboard

13:38without necessarily

13:39having to look at it. So I don't know if

13:41that's 100%, I'm pretty sure that that is

13:43something that

13:44the team thought about. But nonetheless, we

13:46'll have to wait till the feature comes out

13:47to fully

13:48validate that. But data stories was a

13:50really nice feature. Now, I'm not 100%

13:53convinced, I'm never

13:54convinced by features like this, because

13:56what always happens is you want to tweak

13:58them a little

13:58bit, you want to sort of change how it

14:00works. And they did show some capabilities

14:02around dynamism,

14:03so the ability to change things like

14:05filters and have the text update. But we're

14:07going to need to

14:08see this in real life, we're going to need

14:10to see this working. And also, we're going

14:11to need more

14:12details about whether this is actually

14:14going to be part of an add on or not, in

14:15order to really sort

14:16of understand how wide and how far this

14:19feature is going to go. The last part of

14:21this was data

14:22science or business science, which is what

14:25Tableau has essentially branded Einstein

14:27Analytics,

14:28a part of Salesforce that was brought over

14:30to the Tableau product family, and hasn't

14:32really found

14:32its space in the Tableau community, at

14:34least, and it's definitely something that's

14:35used in the

14:36Salesforce world. But again, it's not

14:37something that I'm familiar with. And it's

14:39not something

14:40that a lot of people in the Tableau

14:41community are familiar with. But it looks

14:44like Tableau sort of

14:45recognize this. And what they seem to have

14:47done is they've managed to rebrand the

14:49model building

14:50capabilities that existed in Einstein into

14:53a bit more of a Tableau skin and put it

14:55natively inside

14:56of Tableau. Now, I think there is a catch

14:57with this, I think you're going to have to

14:59have this

15:00only run on Tableau Cloud, because it's

15:02still using the general intelligence that

15:05Salesforce use

15:06to run 150 billion predictions, apparently,

15:09every single day. So that's going to be an

15:12interesting

15:12little tweak. The details here are going to

15:14be super interesting. How is this working?

15:16Is it coaching people appropriately to work

15:18through the data? Because otherwise, you

15:20just

15:20sort of going through model building by

15:22just clicking things. Is the model building

15:24advanced

15:26enough to be really trustworthy? Does it

15:27have enough flexibility to make the people

15:29who do

15:30build models on a day to day basis, happy

15:32with the way that this works, so they can

15:34fully move their

15:35workflow into this setup? It's not entirely

15:37clear. So again, it's one of those things

15:39we'll have to

15:39wait and see. But it was here on the

15:41keynote. And therefore, I think it's

15:42something we're going to

15:43see very soon. Tableau is pretty keen to

15:45bring it in. I'm sure Salesforce want to

15:47bring it in.

15:48And so we're definitely going to see it

15:49very soon, hopefully this year, if not

15:51early next.

15:51Okay, after this section, it basically

15:54turned into Devs on stage. So this to me

15:57was the second

15:57half of the keynote. And then we just

16:00basically got a feature showcase after

16:02feature showcase,

16:03just coming out of pretty much the stage,

16:06it was just awesome to see some of these

16:08features that

16:09we've got to see. So let's just go right

16:11from the top. The first one is shared

16:13dimensions for the

16:14data model. Now, this is not something

16:16radically new in the analytic space. It's

16:18actually a pretty

16:19common feature in other products, Power BI,

16:21and not to mention, but this is now going

16:23to be possible

16:24in Tableau soon, we didn't get an exact

16:26release date, I believe this will probably

16:28come not not in

16:30the next release 2022.2, but probably three

16:33or four, maybe the beginning of next year.

16:36But

16:36nonetheless, it's there and it's working.

16:38It's a simple idea. And that is that a

16:40dimension in the

16:41data model can essentially link to other

16:43dimensions in other logical levels. So it's

16:47as simple as that.

16:48But what this means is you don't have to

16:50build complicated models anymore, because

16:52previously,

16:53you could only have one shared dimension

16:55between two logical tables, because you can

16:57have multiple

16:58dimensions, essentially sharing against

17:00multiple logical tables. And it's going to

17:02be a lot easier

17:03to build data model and make comparisons

17:05that would have been previously a little

17:07bit more

17:08tricky. But as ever, I think this is

17:10something you have to see because we've

17:11been so used to joins

17:13and unions in Tableau that's something like

17:15this, I've just seen people struggle with

17:17the data model

17:18in general. And something even like the

17:20bookstore example that Tableau use is easy

17:23to understand,

17:24because the analogy is easy to understand.

17:26But as soon as you have to apply it to your

17:27data,

17:27people tend to struggle. So I'm going to be

17:29interested to see how Tableau themselves

17:31showcases feature when it actually comes

17:33out. We're going to have a real challenge

17:34trying to

17:35make videos about it here on the channel as

17:37well. So look out for that. The next one

17:39was the web

17:40data connector 3.0. Now this was actually

17:42announced at Trailblazer DX. If you haven't

17:44caught that, go check it out on Salesforce

17:46Plus. Yes, I'm pitching a Salesforce

17:48product. But

17:48nonetheless, and this is actually cool

17:50because it enables a couple of things the

17:53ability to run

17:53connectors locally, rather than having to

17:56have them hosted somewhere on the internet.

17:58And this

17:58essentially means that from a security

18:00perspective, it's a lot easier to get

18:02connectors through the

18:04door. The other thing is easier to build

18:06connectors because of this new SD. And then

18:08lastly, Tableau

18:09talked about the capability of having

18:11something called table extensions,

18:14essentially extensions

18:15that run at the connection level. So the

18:17demo they showed was you connecting to a

18:20data on Twitter

18:21using a web data 3.0 connector, and then

18:24wanting to do sentiment analysis, but not

18:26wanting to do

18:27that inside of the dashboard, actually

18:29wanting to do it at the data level as it

18:31comes in. And so

18:32they opened up essentially a table

18:34extension that allowed you to run Python on

18:36the data. So as the

18:37data gets added in, as it gets refreshed,

18:40the model runs on this particular data

18:42source. And then you

18:43can do the sentiment analysis straight away

18:45inside of Tableau without having to run TAP

18:47I or anything

18:48like that. Be interesting to see how this

18:49actually works in practice, it's not clear

18:51if this is only

18:52going to work for Tableau Online, I think

18:54this will work in most places. And for

18:55Tableau Online,

18:56there'll be probably a managed instance of

18:59Python running somewhere. So be interesting

19:02to see how

19:02this actually works in earnest. But

19:04nonetheless, this is a nice thing to see,

19:06especially for the

19:07data scientists out there who already do a

19:09lot of modeling outside of Tableau, and

19:11then have to sort

19:12of figure out how to blend that with their

19:13Tableau data, whether it's through tools

19:15like Altrix,

19:16or having sort of Python scripts run inside

19:18of Tableau prep, whatever you use, it's

19:21always been

19:21a little bit constant. So now you can do it

19:23at the connection level. Now the next

19:25feature absolutely

19:26blew my mind multi row calculations in

19:29Tableau prep. Now this is like the one use

19:33case that I

19:34think this is so important for is moving

19:37averages and running totals in Tableau prep

19:40, something you

19:41have to do so frequently, it's actually a

19:42very basic thing, you wouldn't think you

19:44need to do

19:44it so frequently. But actually, it's super

19:46important. Let's say you need to do the

19:48running

19:48total over a period of time. And maybe you

19:50want to track when something passes a

19:52target, but you

19:53want to build that into the data source

19:55rather than having it be dynamically done

19:57inside of

19:58Tableau. So then you can compute against

20:00that to avoid doing LODs, which then cause

20:02a performance

20:02issue. That's a very sort of long winded

20:04example. But nonetheless, it's something

20:06that's so easy to

20:07do in other tools like Altrix, as quite

20:09easy to do in SQL, if you know how, but in

20:12Tableau prep,

20:13you have to sort of jump through various

20:14hoops to get it to work. And even then it's

20:16still quite

20:17sort of, you know, constrained, you have to

20:19go out to excel, or you have to go to your

20:21data source and

20:22do a bit of sort of scaffolding to set it

20:25all up no more. And what I really like

20:27about this feature

20:28is that it looks like they've also taken

20:30the time to make it work really nicely, not

20:32just sort of

20:33here's the feature we've done, they've made

20:35it work the way the rest of Tableau prep

20:36works. So

20:37you have a lot of visibility of what's

20:39going on, you get a nice preview. But also

20:41you've got the

20:41ability to do things like add row numbers

20:44to things and fill rows as well. So that's

20:47something

20:47really, really nice and nice little feature

20:49add on from what we got in the past where

20:50you can fill

20:51dates and fill numerical rows. So that's

20:53really, really good to see here. And this

20:55is, this is

20:56going to unlock so much more potential in

20:56Tableau prep. I even tweeted a response to

20:56Jaira Flores to

21:00this to this effect. But yeah, be cool to

21:03see this actually working. And hopefully we

21:05get it later

21:06this year. I can't wait to get my hands on

21:08it. We then moved on to our state of phrase

21:10builder. This

21:11is actually something that was released in

21:1322.1. But this was essentially just

21:16reminding us about

21:17this feature, but more importantly, also

21:20hinting the capability coming soon, which

21:21is going to allow

21:22you to suggest phrases. So not only do we

21:25have the ability to help you build phrases,

21:27but they're

21:27actually going to use machine learning to

21:29look at the previous phrases that have been

21:31run to suggest

21:32possible phrases for you to use. And that

21:34again, will be coming later in the year.

21:37Now, the last two

21:37features that were covered absolute heavy

21:40hitters. The first one is a feature that I

21:42've actually, you

21:43know, seen in the flesh before today, which

21:45is called the data orientation tool. This

21:48is going to

21:48be such an impactful feature, not only

21:50because I think it's actually going to help

21:52people who don't

21:53necessarily build visualizations, but it

21:56will also help authors absolutely helps

21:58everyone. This is

21:59essentially a feature that allows you to

22:01add a little bit of guidance as to how a

22:03dashboard works,

22:04but also shows users how interactions work

22:07without the users necessarily having to

22:10build those

22:10features in or the authors having to build

22:12those features in. But it does it in a

22:13standardized way.

22:14So you can actually train your users to

22:16look at this feature in a standardized way.

22:18And whichever

22:19workbook or dashboard they use, they'll

22:20also be getting some context about the

22:22fields being used,

22:23how the calculations have been done, but

22:25even have links to videos where people can

22:28give demos

22:28of how to use the dashboard. Super, super

22:30useful. I hope this is just version one, I

22:32hope we get to

22:33see more of this feature coming out over

22:35the next few months as well, and releases

22:38as well. And then

22:39the second feature was a really interesting

22:41one. This is essentially image roles for

22:43your data,

22:43the ability to say, look, this column

22:46represents links, and these links actually

22:49link out to images

22:50and then use those images in the data pane

22:52natively, without having to do any hacks or

22:54use

22:54extensions in order to do that. Super

22:56simple, should have been in the product

22:58years ago, but

22:59has only just arrived. And that was

23:01essentially what ended the keynote. Great

23:03note to end it on,

23:04I think people really appreciate something

23:06like that. I can't wait to see what people

23:07do on tablet

23:08public with this. It's going to open up

23:10lots of possibilities, especially for fast

23:12moving consumer

23:12goods, where product images, and product

23:15colors and product, you know, just being

23:17literally being

23:18able to see the product in the context of

23:20the data visualization is going to hugely

23:23help people,

23:24and even things like car parts, even things

23:26like inventory management, that's all going

23:29to be a lot

23:29better. And if you can add on other

23:31extensions as well, and it's going to

23:32really help things sort of

23:34work. I really like it because essentially

23:36allows you to do even cooler things like

23:38hacks, for

23:38example, you could even add QR codes to

23:41those images, you could have a web service

23:43dynamically

23:44or procedurally creating these QR codes.

23:46And there's those QR codes can then do

23:48something

23:48else in another application, there's just

23:50so much more being opened up by that

23:52particular feature.

23:53So I can't wait to see what people do with

23:55that. And it's going to be super fantastic,

23:56especially

23:57have a service that dynamically create

23:59those images based on, you know, some input

24:01from a data

24:02source or whatever. So that would be really

24:04, really cool to see, hopefully in the near

24:05future. But that

24:06was it. That was all the features. That was

24:08everything that was covered in the keynote.

24:10And I think it was absolutely fantastic.

24:12The very end was just a call out some of

24:13the other sessions

24:14that were at the keynote. Now, if you've

24:16made it to the end of this video, thank you

24:17so much. Thank

24:18you for staying and watching this summary.

24:20Please let me know in the comments what you

24:22found

24:23interesting at keynote. If you didn't watch

24:24the keynote, well, great. Hopefully, this

24:26roundup has

24:27helped you. But actually later today, when

24:29this video should come out on time, I'll be

24:31doing a

24:32live stream of the iron vs contest. And if

24:34you haven't already check out my live

24:36stream of the

24:37keynotes two hours long with Andre, we

24:39covered everything we got comments, we had

24:41over 300 people

24:43commenting during the entire live stream.

24:45We even had friends who are watching the

24:47live stream whilst

24:48he was waiting to go into the keynote. So

24:50go and check out the live streams really,

24:52really fun

24:53thing to watch. And you can see what other

24:55people think about the keynote as it went

24:57on. Thanks for

24:57watching this video. Thanks for making it

24:59to the end. Be sure to check out the other

25:01live stream

25:01sessions that we went throughout the week

25:03of conference if you're watching this much,

25:05much further into the future. But

25:07nonetheless, thanks for watching and I'll

25:09catch you in the next video.