Understanding and Utilizing Tableau Pulse

Hey it's Tim here and in today's video I'm going to show you how Tableau Pulse works. As ever let's get stuck in. So I will start off right from the back by saying that Tableau Pulse has just gone into production as it were. It came out of B10, it was launched in 24.1 so I'm recording this essentially almost a week after it's been made public. I did go through a long video going through my first impressions of how it works. If you want a more rough cut of how that experience was go ahead and check out that video. This video is going to try and synthesize everything you need to understand how Tableau Pulse works. So I'm going to pick up from where I left off in my last video where I showed you how to enable Tableau Pulse. Today, I'm going to get straight into the action by going straight into Tableau Pulse. As a refresher, you'll see that once you've enabled Tableau Pulse, you'll see that it turns up here on the left hand side. And when we go ahead and click on that, it takes us through to the experience. So we'll go ahead and click that and you'll see that we land inside of Tableau Pulse. Now, there's a couple of things to bear in mind. I don't have any available metrics and there's nothing for me to browse. So this shouldn't be your first experience if you're using Tableau Pulse, because in essence, you should already have metrics available to you. So the experience I'm going through today is essentially how to build those metrics. In another video, a separate video, I'll go through a more detailed, simpler video on how to use the metrics, if that makes sense. So let's just focus today on how to build the metrics and the metric definitions. And then the next video we'll talk about. how to use them. Okay, so we're here, we've landed in Tableau Pulse. I'm a creator, I'm an author, I need to build metrics for people to use. The first thing you're going to notice is there's a nice big blue call out over here on the right hand side to create a new metric definition. And this is actually quite important because Tableau Pulse breaks down the creation of metrics into two steps. The first one is the creation of a metric definition and the second is the creation of a metric. And Those two kind of happen in one go. If I just open up my sidebar here and I go to this documentation, I'll put a link to this in the description. Tableau have actually done a really good job of detailing this split here in this diagram. I actually really like this diagram. It's a good way to conceptualize the creation of metrics. Whether or not you're building for Tableau Pulse or a dashboard, this is a really good way of thinking about it. So if you look at this example, the metric definition essentially needs three things. It needs a measure, some sort of time dimension, and the data source essentially. And then from that, we're able to add additional context. So once you have those three pieces of information, the additional context, essentially the step two is defined as a metric. And for the metrics, we start to drill into sort of subsets of that specific definition. So if you can see here that down in this metric, we're doing year to date for technology and a couple of other categories. And it's essentially still on sales. And on this one on the right hand side, we're still doing year to date, but instead we're doing it for office supplies. So that is classed as a separate metric, but they're all derived from the same definition. And that's a super important thing to understand. So when you go ahead and build for the first time, think about your definition, and then you can enhance that with various metrics that feed off that original definition. You'll see this later on in the video. I'll call it out. But if we head back to Tableau Pulse, when we go ahead and hit the new metric definition, you'll see we get a list of data sources. Now, in my previous video, I highlighted... that the data sources you see here are from your Tableau Cloud instance. Don't forget, Tableau Pulse is not available for Tableau Server, so you can't get these from Tableau Server. They're only from Tableau Cloud. And I've actually got a data source which has my YouTube analytics that has essentially been piped into Snowflake from Frivetran through the YouTube API. So we'll go ahead and click on that and hit connect. And once we hit connect, we get straight into the definition building experience. Let me close my sidebar so you get a bit more space to see this. Now. Let me just call out a few things. When you land in this space, there's two parts of the journey. There's the definition, which is what we're going to do first. And then there is the insights. The insights are more of a behavior of how the metric works with the metric definition. And so we'll come to the insights a little later once we've built out this metric definition a little bit more. The next thing you'll see if I just switch to red here from a highlighter is the data source. The data source is essentially what you've just connected to. And what I will say is that it's important to... really pay attention to metadata, I think, in this product, because that information is used throughout the product to do different things. So I'm going to call this subscribers. And we're going to say that this metric definition tracks subscribers. Again, notice my language. I'm calling this the metric definition rather than just the metric. So tracks subscriber change month to month linked to videos. That's exactly what this metric does. It's sort of a weird way of the way YouTube API works. It actually pins most subscribers to a specific video unless you just subscribe out of your own free will. Let's go ahead and hit full stop on that. And we've defined the metric definition. We've defined the description. Let's have a look at the measures here. And so here, when we click on the dropdown, you can see it's pulling from the data source. And the thing I'm interested in here is subscribers. So as soon as I start typing, you can see it searches this. Now, for this particular metric, There's a problem. I have subscribers gained, I have subscribers lost, but what I don't have is a net subscriber count. So let me do two things. Let's assume that's not a problem. Let's just hit subscribers gained and you'll see that it automatically fills the aggregation and the type of math that's going to work. So you see here running total works out of the gate and you get non-cumulative as well there. And so we can select one of these and you can start to sort of play around with this. Now, the key thing. you're missing is a time dimension. Don't forget we needed a measure, a time dimension, and then a data source. We've got a data source, we've got a measure, the last thing is a time dimension. So for this, this is actually linked to the date that the data is being collected on. So if I select that date, as soon as we give it all three pieces of information, we immediately get a metric applied. Now again, notice I said a metric, because what is strictly happening here is that this on the left hand side is your definition. And this on your right hand side is actually a metric. It's just lacking some sort of specificity, if that makes sense. The specificity we have at the moment is month to date. You could choose another time context, but month to date is a default context. So it's sort of an interesting one because you have this sort of unified interface. But you have to really remember that on the left hand side, you're dealing with the definition. On the right, you're dealing with the metric. And those two are not the same. I'll explain why that is the case later in this video. So please bear with me and you'll see why this is an important thing to understand. Okay, so now that we've done this, we can go down and you can see you get a few other options and you can kind of get the gist of how this works. It's actually quite easy to set up the metric. That is it. That's done. I mean, I didn't even sort of celebrate that that's how easy it was. And it really was that easy. And I'm not just a fanboy here, just a championing tableau. This is really a very accessible way of... creating metrics in a quick digestible manner. Now remember earlier on we said we had a problem and this was with this metric subscribers gained and subscribers lost. What I'd actually like to do is to create a new metric here called net subscribers but you'll notice there's no interface for me to do a calculation just yet. So in this value area here if you scroll down because this right hand space is the definition one of the things you can do is you can create what's called an ad. advanced definition. You can see that right here. Okay. And if we go ahead and click on that, what it does is it takes us to something very familiar to desktop creators. And that is the ability to just go into Tableau and build your metric. You'll notice that my data source is actually a data model across two data sets, and I can go and access every single field as I would do. And the way this works is very similar to the experience you get with published data sources in web authoring. You're essentially able to go ahead and create your published data source. you can model what you're looking at here on the right-hand side in the canvas, but it never creates those charts. It's just an area where you can model things. What we can do here, we can create a calculation and we can say sum of subscribers gained, minus sum of subscribers lost. Now that we've done that, we can call this net subscribers. and we'll give that a bit of a space there. Net subscribers, that is our metric. That is a much better way of doing this. We'll hit Apply, and we'll hit OK, and you'll notice nothing has changed because we've just done what we do in Desktop. We've created a metric down here, okay? Now, to build that metric, notice the same three things that we needed before are also present. We've already got the data source. That's part of the definition. What we now need to add to this view is the measure and the time dimension. So go ahead. and let's drag the net subscribers to the measure. And you'll see that we immediately get a bar chart telling us something, so 3,000. And if this is all we did, the metric would just track this number. This is not a good reflection of my actual subscriber count because the data source only goes back a bit of a few months because of the way that Fivetran and YouTube API work. So let's go ahead and grab a date, and the date we want here is date day. And just like you can do in Tableau, you can... choose the context for that date. So rather than the year, I'm actually going to go back down here and choose a continuous day, if that makes sense. So we get a day by day blow of that. And there you go. That's something a little bit more familiar. Now, this chart is a representation of what's driving the pulse metric, but it's not actually the pulse metric. It's just a visual way for you to see some context. So what do we do from here? Well, we can go ahead and hit apply. And before I actually do that, notice that... you can do some filtering on this metric in here. This is not the same as letting users choose the filtering, if that makes sense. A good way to think of it is if I was building this advanced metric and what I wanted to do is exclude certain videos or exclude certain subsets of my data from being part of this metric, I could actually do that here in the advanced elements. I can go ahead and get the video title. Let's say that I didn't want a specific video to contribute to this. Let's say as I go to what is Tableau. The reason I might exclude this is because this is the biggest video on my channel. So it has a rather large skew on what's going on. So if I hit OK and we say exclude and we hit apply, you'll see in the background the metric changes. But the biggest change was actually in the axis. And you can see that that's now taken into effect. And as soon as I remove it. my metrics sort of adapts to adjust for that. It's a very slight change, but in the more recent months, it hasn't had a bigger impact. In the previous months, it's like 50% of my channel grades. So we'll just leave this at this and we'll hit apply. Now, when you hit apply, you get a reminder about your selections. This is because If you don't do all these three things, you'll get an error. So this is like a nice way of reminding you that this is what you need. We have all of these. We have a measure. We have a time dimension. We don't need filters. It's optional. So we'll hit apply. And that is how you get around that problem of being able to create a metric from a calculation inside of this window. And you'll see that this is now a little bit better. It's a lot a bit clearer and we get a better view of what's going on. Now, one thing I didn't touch on in that step is that we have a bit of an issue with the... running totals inside of that. If I go to replace advanced definition and instead of the standard measure I've got here, I go and do a running total, you'll see that it generates a running total fine. But if I hit apply and I hit apply again, I get a bug. And I don't know if this is an issue just because it's out of the gate, but I've had this sort of bug consistently since I've been using Tableau Pulse. And admittedly, it's only been public for one week. So I'm sure this will get fixed. But nonetheless, I just wanted to call that out if you're having that experience. Okay. So let's go ahead and undo that change. Let's go ahead and remove the running total and hit apply. And now if we hit apply again, you'll see it magically works. There's no problem now. And we get back. So that is our advanced definition. Now, the way the measure works, you kind of get some nasty sort of Tableau stuff in the background. You'll see that it doesn't call it what I called it, which was net subscribers. It calls it calculation 105, whatever. So that's always something that happens sometimes. If you look in the Tableau workbook XML, you can see that kind of. coming through here in the product. But nonetheless, just be aware that these are just sort of, I guess, sort of rough edges that will get smoothed out over time. But nonetheless, the metric is working fine. The second part of this is then telling Tableau Pulse how to interpret those insights. And this is the easiest part to miss, I believe, because you can go ahead and hit save definition. But I think you have to get into the habit of going into the second tab, because if you go into the second tab, you'll notice that there are no insights to preview right now. What's happening is in the background, Tableau is already processing this information. So we'll go ahead and it will do this quite quickly and we'll be able to come back to this and look in the future. But you can tell Tableau here what happens when the value is going up. Obviously, what happens in the other direction is implied. So we don't need to always specify that. But nonetheless, you can tell if going up is favorable, which it is in this case. And you can also change the insight. type. So you get these several insight types here. So you've got five, six insight types, and you get a little bit of a description of what's going on and the different types of insights that you can get. And you can disable certain ones. If that insight type doesn't work, you can disable them. You can just change them and switch them off. So you do have a bit of control into that. Now, if we go back into the definition, what I want to do is finish building this metric because once we finish defining the... definition everything else defines additional metrics okay so it's it's not super clear to me but i i sort of figured this out over time these options down here kind of drive that behavior so the number format is just a general sort of description of the number and if you click on this you do get the ability to change to currency or percentage and you can you can kind of um use a description. So we can say unit expression singular. So you can say subscriber, and we can say here subscribers, and that is it. Now, you'll notice that nothing really changes here. Nothing really changes in the definition. I think this will have a big play further down the line. This bit here, this is where I think stuff really matters because the dimensions you add here end up being what? end users can use to customize their metrics essentially so the definition you give has to include these dimensions otherwise users can't really build segmented metrics for themselves for example if i was using superstore i couldn't use the categories to generate a metric for each category so in my case i will use a video title because i want to be able to create metrics for a specific video I might also use other information about the channel. So I might say, as a very simple example, the channel title, if I was tracking multiple titles, I might also use, let's say, tags. Tags is something that I think we do get in here. I don't know why I'm scrolling down. I can just go and search these things. And then the final thing I might want to do, I think that's honestly enough, actually. Those, those... Those are enough to show you what's happening. And you can see that they get added here at the top. So you can kind of think of everything that I'm sort of circling in this blue box as being part of your metric definition and your metric control all in one package. And as soon as you're done, we can go ahead and hit save. Let's hit save definition. Here we are. We've built our metric definition, and the first thing you get is actually a metric out of the gate, and you can see it immediately has insights. I think that's a super powerful thing here. I've just added the data source and the value comes out of the system straight away. I can immediately start working with this. I don't know if it processes it in the background and in the time I've taken to talk to you it's done it, but nonetheless, it's here. Now, I will use this opportunity to just send a bit of feedback to Tableau. This back button, it's wild because in this particular instance, it sends you back to the metric definition. It's always contextual to where you've just come from, which means depending on where you are across the whole of Tableau Pulse, that back button can mean different things. I initially thought this back button was going to go to Tableau Pulse, the landing page, so I could see all my other metrics, but you'll see that if I hit back, it goes back to the metric definition and it asked me to select the data source. which is slightly odd. I just didn't expect it to go right to the beginning of the previous experience. If anything, I would expect it to go back to the editing experience of the metric I've just created. Nonetheless, this is slightly odd and it can leave people confused and thinking, hey, what happened? And then when you hit close, you go back to Tableau Pulse and you're landing on this page and you're like, hey, where's the metric I just created? It's not here. So here's the thing. The metrics you've just created you've not yet had a chance to follow said metrics. So if we go to browse metrics, you'll see that that metric is indeed there. If I click on it, I do actually get to see this. And remember earlier on when I said that you create your definition and your first definition, you get a free metric with it. Essentially that first metric is the same as the definition without any segmentation. So what does that mean? Well, let's go to this metric and let's add some segmentation and you'll see how you can save additional metrics having defined them. So we'll go ahead to this, we'll hit adjust, and then we can go ahead and start searching for specific things. So if I want to find all my videos that say Tableau Pulse, you'll see that it's able to go through and we can go ahead and just tick all of these and we'll hit OK. These are the five. So those five videos are specifically about Tableau Pulse and they're all from my channel. There's nothing special there. Unfortunately. I'll come back to this point later, but if you've not done your data prep, it will show here. So the tags are not in the format I was expecting. I was expecting them to be sort of separate items, but they're all just sort of everything I put into that space in YouTube. So it's not perfect. But nonetheless, we won't use that. I can choose different contexts of time as well. This is super important. Depending on the context you have, you can choose week to day. And, you know, this changes the metric. So as soon as I hit this tick. What that does is it saves an instance of a metric. And you'll see in the last week, nothing has happened. And a lot of you will see this the first time you use Tablet Pulse because your data has to be running to today's date. If you look at this, Tablet Pulse is always basing itself on today. And if your data doesn't have anything today, this is what you'll see. However, if I go back and I adjust this metric, let's say we don't want to do week to date, let's do month to date, and we hit plus. then you'll see that we do get some information back and it stops right here okay and this is this is super useful because um i i spent about five minutes for the first time just trying to understand what was going on and i couldn't i figure it out and i realized oh it's because there's no so there's no there's no data in the context that i have so here we have the information these are just the videos related to tableau pulse so over the last month and there are about 22 subscribers who've come from videos relating to Tableau parts. Now we've done this a couple of times, we've created variations of this metrics a couple of times. So let's go back and again when you hit back this time it takes you somewhere different to where I'd expect. Notice that rogue instance where we created a metric that didn't have anything in it, that was instantiated immediately. You didn't have really an option to save it or delete it and that's been created and the most recent one we created is also here so 22 here as well. So There's a little bit of housekeeping you have to do. If you're just busy clicking these metrics and not sort of paying attention, you can come back here and find you've got three or four metrics you didn't intend to have. So you can obviously manage those by just going here, seeing the details. And as soon as you go to the details, you can go back in there and actually go ahead. I thought you could delete them here, but actually that's wrong. What am I missing here? Okay, I thought you could delete it here. Maybe I'm missing something. I could swear. I found a way to delete a metric, but maybe I was deleting metric definitions. And so maybe this will come back to me, but. Hope hope you can delete these rogue ones because you saw how easy it was for me to create this null metric and they're kind Of frustrating as well because they don't need to get experience and if they're discoverable then hey You don't want people to be seeing these but nevertheless This is this is sort of the experience now Let me go ahead and hit follow on these two and if I go back to the tableau pass landing page by hitting that You'll see that those two metrics are created now land here on my landing page. So We've got these nice metrics available to us here, and we can kind of just get using them. So if I go back into the subscribers, this is it. This is how it's working. Now, at any point, if you want to change this, if you want to play around with this, if you click on these three dots at the top, you always get the option to edit the definition. And that takes you back to this experience. And you can obviously go back and change the insights. And when you do this, it changes the context each time. This is also a good place to go back to this insights tab and show you that now it's generated some context. And what these really lend themselves to are the different types of insights that Tableau Pulse can generate. We've already been going for 20 minutes here, so I don't want to make this video longer by going into the different types of insights you can get. I'll do this in a separate video, but just be aware that there's a broad range of insight types and they generally map to these ones that you can see here. But in terms of how they play out, it probably helps to be able to see how those interactions work. So I'll come back to that a little later. The other thing I'll also highlight as I sort of scroll up and down here. is that look, if you've not done your data prep upfront, this is just still not going to give you nice results. You can see here that the tags, the tags are just causing so much noise in here. There's valuable information because I use these tags on videos where it makes sense, but they're just not being cleansed properly. What I would love to do is to have a way of being able to use this information and just pass this out so tablet can understand that although these are lists, actually all we care about is the items in each of these, in each of these. a list of values, arrays of values, as it were, if you're a programmer. So it's just a little bit something sort of to bear in mind. If you're not doing a data prep up front, you're going to have to do it in Tableau Prep, Tableau Desktop in your data source, or do it further back somewhere more observable in something like DBT or in a data engineering operation that you're running. Okay. The other thing I have to say about this, if I just go back and save this, we'll just save this as is, we haven't really changed anything, is... I would like the ability to be able to put what I would call a wildcard in here that updates as a data update. So at the moment, you can see the video title here. I can go ahead and type, you know, Tableau desktop and all the videos related to Tableau desktop come up. Now, the problem is, is, you know, when I when I deselect one, it deselects. And if I hit exclude, it excludes all of them. So if I do exclude and then. I just sort of delete this. You see that it says that all of them have been excluded. So there's no way for me to do like a wildcard search on the data set, if that makes sense. There's no way for me to say anything that mentions this specific term always added to this metric because then I think that makes metrics a little bit more meaningful and it makes these dropdowns actually represent what we can do already inside of Tableau today. So that would be one additional thing I'd love to see in the future. But nonetheless, I'm not gonna create a new metric. I don't wanna create more noise. Right. The very final thing I know we've been going for some time, we're nearly 30 minutes in, is at this section here. This is where really the magic starts to happen. If we spend a bit of time just working with this metric, you can see that obviously we've got the overview and the breakdown in here. And if we go to the breakdown, we actually get a little bit more of a detailed breakdown. And you can see this is a genuine reflection of my channel. The Tableau Desktop Crash Course is driving a good number of subscribers each month. And if we go down the list, Other videos have a slightly smaller impact, but nonetheless, this is very representative of what I know and what works. If I select video tags, though, you can see the tags again are a bit noisy. And this makes us basically pointless because a large bunch don't have a value and the rest are just I mean, what can I really do with that? OK, it's not much. It's too much information. I'll go back to the overview. You can obviously hover over this and work with it, which is quite nice. And I like the fact that this is contextualized. I do need to get my data source to update a little bit. So there's a little bit of an issue with my sort of data pipeline in the background. But here's the next really sort of exciting things. This section here is where the AI comes in. So they call it GAI, so generative AI, right? These questions are part of sort of a system that Tableau's built where essentially the way that the platform works is the insight is actually generated from your raw data. That is just, you just think of it as maths being done on your data. And essentially those are facts. Those facts are then presented in order of preference, in order of sort of what's working and what's not. And then once that's done. It's summarized by generative AI. And then what you get back is essentially these sentences. And these sentences are a good way of helping the user go to the next question, understand what's going on. And so the computations that drive these questions have already been done in the background. But what these questions are is sort of tempting you to explore those journeys, take those journeys with your data. So if we go ahead and say, OK, which video title decreased the most? Which video title had the most negative impact on my subscriber count? you can see here that it's actually what is Tableau. And this makes sense because the way you have to think of this metric is that the metric isn't about which video lost me subscribers. Remember, our metric was actually net subscribers. It's not subscribers lost. It's not subscribers gained. It's net subscribers. So I could go ahead and recreate this with subscribers lost. And this sentence would make more sense. But all it's saying is that I got 19 less subscribers this month compared to last month for this particular video. Okay. And it gives us a nice sentence that actually breaks that down a little bit. And remember all the terminology we did before for singular versus plural. That's all in here. That's all being used to kind of make this work really, really well. And as we click on these, notice every time I click on something here, it gets added just below here. Okay. So let's go ahead and see which video title had high subscribers. So let's go ahead and hit that. Again, you get the Tableau Desktop Crash Course. You'd already seen that. And. As you click on these, the metrics sort of go down. So I can kind of just click on these and you'll see that all the metrics sort of come through. And remember, some of these were some of the noisy ones we were seeing on the insights tab before. So that was already a preview of what you were going to see. And it's essentially just enabling and disabling them behind the scenes. So it's a pretty good platform. And, you know, my data is pretty simple. I'm just tracking one thing, subscribers. But in Superstore and in other data sets, you might have slightly richer context that you can work with. One thing I will say, if you're working with Superstore, make sure you shift the dates to the last day is actually today. Because if you don't do that, you'll see null for quite a lot of the Superstore data because it stops at a certain point in time depending on the tablet release. So let's go back. That is pretty much the whole entire experience in a nutshell. That is how to use the platform. What I will say is this, if I go back to the tablet past landing page, now that I'm here, you'll notice that this summary here at the top, being generated. So it kind of tries to pull out the most important things happening. So it says this month, there is a 5.9% decrease in subscribers based on this video. So what is Tableau explaining under 10 minutes? So basically it's saying, hey, there's a 6% decrease in this one video compared to last month. However, there is a significant increase, 28.3% in overall subscribers compared to the same time last month. So in broad brush terms, I'm doing well, but being specific, there's one video that's... got an impact. So I might choose to go and analyze that. I might choose to go and do something else. Now, unlike other features in Tableau, these thumbs up and thumbs down help improve the system. Tableau is using these as prompts to try and understand what people are interested in and what they're not. So if I say that this is good, you can obviously send that feedback to Tableau. I won't bother here. But what this will help you do is try and understand what's going on. Other things to bear in mind, you'll see this says it was last updated 12 hours ago, and that's because I'd already created this data set whilst doing a demo. So this sentence suggests a couple of things, and it's sort of a really intriguing fact about Tableau Pulse and how it's working behind the scenes. 12 hours ago, I'd just finished recording what was the third take of this video, right? And what's ended up happening is it somehow cashed... that data source and it's remembered that it's seen this this data source before likely because it's linked to my tableau cloud instance so rather than regenerating all the insights it actually found that it already generated them and it's simply serving them up from the cache even though you've watched me create these metrics for the first time and add the data source for the first time to tableau pulse whilst doing this so it does suggest a little bit of caching a little bit of what I would suggest sort of frequency in which it's going to be updating these metrics based on how often the data source is updated. So if the data source isn't updated, I don't expect this to change, but if it's updating frequently, then I would expect tablet paths to hopefully pick up on this frequency. Anyway, these are small nuances to bear in mind as we start to get to know this feature a little bit more, but nonetheless, I think that is pretty much all I want to cover today. We've been going for a long time, 30 minutes. It's a really long time for a video. Dude, thank you for watching this. If you've watched it all the way through, let me know what feedback you have about this video, about the feature below. I do know the Tablet product team do see the comments. So go ahead, let them know what you think. Save me the sort of job of having to summarize it for them. But the other thing to bear in mind here is there's so much more to discover. So if you've discovered something, you find it super useful, if you've got some questions and you'd want to sort of find out, you know, how to execute that. Let me know in the comments below. We'll try and see what we can do in the coming days. I need to spend a bit more time generating a bigger range of metrics and a bigger range of insights. So I'm slowly working through building a bunch of datasets that are going to slowly update over time. And we're going to try and use Tableau Pulse to see how well it passes out some of that information. That's super important in this particular case, because I think this is a new feature it's going to have. a lot, a lot of sort of strange edges and rough edges that we need to sort of iron out. The last thing I'll say, though, is that at least on this release, now that it's public, there are a few features missing from Tablet Cloud that I would have expected to be in here. Specifically, if you're paying for something like the data management add-on, I would have hoped to have seen more information about lineage. If I go to a metric, for example, I would really hope that once I'm here... I start to see a little bit of information relating to lineage, maybe some charts and dashboards that use the related metrics so that I can go off and see the same context inside of the Tableau cloud world. Now, I do know that it's a deliberate choice by Tableau to make Tableau Pulse a separate experience, so it doesn't have to be encumbered by all the effort and all the sort of legacy that is Tableau cloud and Tableau server. But at the same time, I think it's a normal expectation, especially in the most recent years where Tableau and We've been really pushing the data management add-on to lots and lots of customers to really bring that value through to new platforms. Otherwise, it does sort of beg the question of, you know, when you subscribe to these things, how secure is your investment if they're not being pulled through to new features? You know, if you'd used Ask Data or Metrics in the past and you've spent the last three years finding a sweet spot where these work, great. I do think Pulse is a better product than Metrics, definitely. But all the less, you know, the time you've invested in that. kind of you know doesn't really pay off here it's a completely different experience you have to reset your expectations you have to rebuild you the way it works the other final thing is that we will do a video on how to use this as an end user some of the feedback i get is that look a lot of my videos are great for authors but what about just end users who don't care about building these things i'm just going to come and use these metrics we will do a dedicated video on that just to make it easy for everyone to be able to share that as well okay we've been going for long enough And I really hope I haven't missed anything. That's sort of my biggest nightmare. This is the fourth time I've recorded this. And so I think I've done it in a much more logical order this time around. So this is just, you know, an honest, honest experience. Let me know what you think. Let me know if there's anything missing whatsoever. We can cover it later on this week. As ever, thanks for watching and I'll see you in the next video.

I did go through a long video going through my first impressions of how it works. If you want a more rough cut of how that experience was go ahead and check out that video. This video is going to try and synthesize everything you need to understand how Tableau Pulse works.

So I'm going to pick up from where I left off in my last video where I showed you how to enable Tableau Pulse. Today, I'm going to get straight into the action by going straight into Tableau Pulse. As a refresher, you'll see that once you've enabled Tableau Pulse, you'll see that it turns up here on the left hand side.

And when we go ahead and click on that, it takes us through to the experience. So we'll go ahead and click that and you'll see that we land inside of Tableau Pulse. Now, there's a couple of things to bear in mind.

I don't have any available metrics and there's nothing for me to browse. So this shouldn't be your first experience if you're using Tableau Pulse, because in essence, you should already have metrics available to you. So the experience I'm going through today is essentially how to build those metrics. In another video, a separate video, I'll go through a more detailed, simpler video on how to use the metrics, if that makes sense.

So let's just focus today on how to build the metrics and the metric definitions. And then the next video we'll talk about. how to use them. Okay, so we're here, we've landed in Tableau Pulse.

I'm a creator, I'm an author, I need to build metrics for people to use. The first thing you're going to notice is there's a nice big blue call out over here on the right hand side to create a new metric definition. And this is actually quite important because Tableau Pulse breaks down the creation of metrics into two steps. The first one is the creation of a metric definition and the second is the creation of a metric. And Those two kind of happen in one go.

If I just open up my sidebar here and I go to this documentation, I'll put a link to this in the description. Tableau have actually done a really good job of detailing this split here in this diagram. I actually really like this diagram.

It's a good way to conceptualize the creation of metrics. Whether or not you're building for Tableau Pulse or a dashboard, this is a really good way of thinking about it. So if you look at this example, the metric definition essentially needs three things.

It needs a measure, some sort of time dimension, and the data source essentially. And then from that, we're able to add additional context. So once you have those three pieces of information, the additional context, essentially the step two is defined as a metric. And for the metrics, we start to drill into sort of subsets of that specific definition. So if you can see here that down in this metric, we're doing year to date for technology and a couple of other categories.

And it's essentially still on sales. And on this one on the right hand side, we're still doing year to date, but instead we're doing it for office supplies. So that is classed as a separate metric, but they're all derived from the same definition.

And that's a super important thing to understand. So when you go ahead and build for the first time, think about your definition, and then you can enhance that with various metrics that feed off that original definition. You'll see this later on in the video.

I'll call it out. But if we head back to Tableau Pulse, when we go ahead and hit the new metric definition, you'll see we get a list of data sources. Now, in my previous video, I highlighted... that the data sources you see here are from your Tableau Cloud instance. Don't forget, Tableau Pulse is not available for Tableau Server, so you can't get these from Tableau Server.

They're only from Tableau Cloud. And I've actually got a data source which has my YouTube analytics that has essentially been piped into Snowflake from Frivetran through the YouTube API. So we'll go ahead and click on that and hit connect. And once we hit connect, we get straight into the definition building experience.

Let me close my sidebar so you get a bit more space to see this. Now. Let me just call out a few things.

When you land in this space, there's two parts of the journey. There's the definition, which is what we're going to do first. And then there is the insights. The insights are more of a behavior of how the metric works with the metric definition.

And so we'll come to the insights a little later once we've built out this metric definition a little bit more. The next thing you'll see if I just switch to red here from a highlighter is the data source. The data source is essentially what you've just connected to.

And what I will say is that it's important to... really pay attention to metadata, I think, in this product, because that information is used throughout the product to do different things. So I'm going to call this subscribers. And we're going to say that this metric definition tracks subscribers.

Again, notice my language. I'm calling this the metric definition rather than just the metric. So tracks subscriber change month to month linked to videos.

That's exactly what this metric does. It's sort of a weird way of the way YouTube API works. It actually pins most subscribers to a specific video unless you just subscribe out of your own free will.

Let's go ahead and hit full stop on that. And we've defined the metric definition. We've defined the description. Let's have a look at the measures here.

And so here, when we click on the dropdown, you can see it's pulling from the data source. And the thing I'm interested in here is subscribers. So as soon as I start typing, you can see it searches this.

Now, for this particular metric, There's a problem. I have subscribers gained, I have subscribers lost, but what I don't have is a net subscriber count. So let me do two things. Let's assume that's not a problem.

Let's just hit subscribers gained and you'll see that it automatically fills the aggregation and the type of math that's going to work. So you see here running total works out of the gate and you get non-cumulative as well there. And so we can select one of these and you can start to sort of play around with this. Now, the key thing.

you're missing is a time dimension. Don't forget we needed a measure, a time dimension, and then a data source. We've got a data source, we've got a measure, the last thing is a time dimension.

So for this, this is actually linked to the date that the data is being collected on. So if I select that date, as soon as we give it all three pieces of information, we immediately get a metric applied. Now again, notice I said a metric, because what is strictly happening here is that this on the left hand side is your definition.

And this on your right hand side is actually a metric. It's just lacking some sort of specificity, if that makes sense. The specificity we have at the moment is month to date. You could choose another time context, but month to date is a default context.

So it's sort of an interesting one because you have this sort of unified interface. But you have to really remember that on the left hand side, you're dealing with the definition. On the right, you're dealing with the metric. And those two are not the same.

I'll explain why that is the case later in this video. So please bear with me and you'll see why this is an important thing to understand. Okay, so now that we've done this, we can go down and you can see you get a few other options and you can kind of get the gist of how this works. It's actually quite easy to set up the metric. That is it.

That's done. I mean, I didn't even sort of celebrate that that's how easy it was. And it really was that easy. And I'm not just a fanboy here, just a championing tableau. This is really a very accessible way of...

creating metrics in a quick digestible manner. Now remember earlier on we said we had a problem and this was with this metric subscribers gained and subscribers lost. What I'd actually like to do is to create a new metric here called net subscribers but you'll notice there's no interface for me to do a calculation just yet. So in this value area here if you scroll down because this right hand space is the definition one of the things you can do is you can create what's called an ad. advanced definition.

You can see that right here. Okay. And if we go ahead and click on that, what it does is it takes us to something very familiar to desktop creators. And that is the ability to just go into Tableau and build your metric.

You'll notice that my data source is actually a data model across two data sets, and I can go and access every single field as I would do. And the way this works is very similar to the experience you get with published data sources in web authoring. You're essentially able to go ahead and create your published data source. you can model what you're looking at here on the right-hand side in the canvas, but it never creates those charts.

It's just an area where you can model things. What we can do here, we can create a calculation and we can say sum of subscribers gained, minus sum of subscribers lost. Now that we've done that, we can call this net subscribers. and we'll give that a bit of a space there.

Net subscribers, that is our metric. That is a much better way of doing this. We'll hit Apply, and we'll hit OK, and you'll notice nothing has changed because we've just done what we do in Desktop.

We've created a metric down here, okay? Now, to build that metric, notice the same three things that we needed before are also present. We've already got the data source.

That's part of the definition. What we now need to add to this view is the measure and the time dimension. So go ahead.

and let's drag the net subscribers to the measure. And you'll see that we immediately get a bar chart telling us something, so 3,000. And if this is all we did, the metric would just track this number. This is not a good reflection of my actual subscriber count because the data source only goes back a bit of a few months because of the way that Fivetran and YouTube API work. So let's go ahead and grab a date, and the date we want here is date day.

And just like you can do in Tableau, you can... choose the context for that date. So rather than the year, I'm actually going to go back down here and choose a continuous day, if that makes sense. So we get a day by day blow of that.

And there you go. That's something a little bit more familiar. Now, this chart is a representation of what's driving the pulse metric, but it's not actually the pulse metric.

It's just a visual way for you to see some context. So what do we do from here? Well, we can go ahead and hit apply. And before I actually do that, notice that...

you can do some filtering on this metric in here. This is not the same as letting users choose the filtering, if that makes sense. A good way to think of it is if I was building this advanced metric and what I wanted to do is exclude certain videos or exclude certain subsets of my data from being part of this metric, I could actually do that here in the advanced elements. I can go ahead and get the video title.

Let's say that I didn't want a specific video to contribute to this. Let's say as I go to what is Tableau. The reason I might exclude this is because this is the biggest video on my channel.

So it has a rather large skew on what's going on. So if I hit OK and we say exclude and we hit apply, you'll see in the background the metric changes. But the biggest change was actually in the axis.

And you can see that that's now taken into effect. And as soon as I remove it. my metrics sort of adapts to adjust for that. It's a very slight change, but in the more recent months, it hasn't had a bigger impact.

In the previous months, it's like 50% of my channel grades. So we'll just leave this at this and we'll hit apply. Now, when you hit apply, you get a reminder about your selections.

This is because If you don't do all these three things, you'll get an error. So this is like a nice way of reminding you that this is what you need. We have all of these. We have a measure. We have a time dimension.

We don't need filters. It's optional. So we'll hit apply. And that is how you get around that problem of being able to create a metric from a calculation inside of this window. And you'll see that this is now a little bit better.

It's a lot a bit clearer and we get a better view of what's going on. Now, one thing I didn't touch on in that step is that we have a bit of an issue with the... running totals inside of that. If I go to replace advanced definition and instead of the standard measure I've got here, I go and do a running total, you'll see that it generates a running total fine. But if I hit apply and I hit apply again, I get a bug.

And I don't know if this is an issue just because it's out of the gate, but I've had this sort of bug consistently since I've been using Tableau Pulse. And admittedly, it's only been public for one week. So I'm sure this will get fixed. But nonetheless, I just wanted to call that out if you're having that experience.

Okay. So let's go ahead and undo that change. Let's go ahead and remove the running total and hit apply.

And now if we hit apply again, you'll see it magically works. There's no problem now. And we get back. So that is our advanced definition.

Now, the way the measure works, you kind of get some nasty sort of Tableau stuff in the background. You'll see that it doesn't call it what I called it, which was net subscribers. It calls it calculation 105, whatever. So that's always something that happens sometimes.

If you look in the Tableau workbook XML, you can see that kind of. coming through here in the product. But nonetheless, just be aware that these are just sort of, I guess, sort of rough edges that will get smoothed out over time. But nonetheless, the metric is working fine.

The second part of this is then telling Tableau Pulse how to interpret those insights. And this is the easiest part to miss, I believe, because you can go ahead and hit save definition. But I think you have to get into the habit of going into the second tab, because if you go into the second tab, you'll notice that there are no insights to preview right now. What's happening is in the background, Tableau is already processing this information.

So we'll go ahead and it will do this quite quickly and we'll be able to come back to this and look in the future. But you can tell Tableau here what happens when the value is going up. Obviously, what happens in the other direction is implied.

So we don't need to always specify that. But nonetheless, you can tell if going up is favorable, which it is in this case. And you can also change the insight. type. So you get these several insight types here.

So you've got five, six insight types, and you get a little bit of a description of what's going on and the different types of insights that you can get. And you can disable certain ones. If that insight type doesn't work, you can disable them.

You can just change them and switch them off. So you do have a bit of control into that. Now, if we go back into the definition, what I want to do is finish building this metric because once we finish defining the... definition everything else defines additional metrics okay so it's it's not super clear to me but i i sort of figured this out over time these options down here kind of drive that behavior so the number format is just a general sort of description of the number and if you click on this you do get the ability to change to currency or percentage and you can you can kind of um use a description.

So we can say unit expression singular. So you can say subscriber, and we can say here subscribers, and that is it. Now, you'll notice that nothing really changes here.

Nothing really changes in the definition. I think this will have a big play further down the line. This bit here, this is where I think stuff really matters because the dimensions you add here end up being what? end users can use to customize their metrics essentially so the definition you give has to include these dimensions otherwise users can't really build segmented metrics for themselves for example if i was using superstore i couldn't use the categories to generate a metric for each category so in my case i will use a video title because i want to be able to create metrics for a specific video I might also use other information about the channel. So I might say, as a very simple example, the channel title, if I was tracking multiple titles, I might also use, let's say, tags.

Tags is something that I think we do get in here. I don't know why I'm scrolling down. I can just go and search these things. And then the final thing I might want to do, I think that's honestly enough, actually. Those, those...

Those are enough to show you what's happening. And you can see that they get added here at the top. So you can kind of think of everything that I'm sort of circling in this blue box as being part of your metric definition and your metric control all in one package. And as soon as you're done, we can go ahead and hit save.

Let's hit save definition. Here we are. We've built our metric definition, and the first thing you get is actually a metric out of the gate, and you can see it immediately has insights.

I think that's a super powerful thing here. I've just added the data source and the value comes out of the system straight away. I can immediately start working with this.

I don't know if it processes it in the background and in the time I've taken to talk to you it's done it, but nonetheless, it's here. Now, I will use this opportunity to just send a bit of feedback to Tableau. This back button, it's wild because in this particular instance, it sends you back to the metric definition.

It's always contextual to where you've just come from, which means depending on where you are across the whole of Tableau Pulse, that back button can mean different things. I initially thought this back button was going to go to Tableau Pulse, the landing page, so I could see all my other metrics, but you'll see that if I hit back, it goes back to the metric definition and it asked me to select the data source. which is slightly odd. I just didn't expect it to go right to the beginning of the previous experience.

If anything, I would expect it to go back to the editing experience of the metric I've just created. Nonetheless, this is slightly odd and it can leave people confused and thinking, hey, what happened? And then when you hit close, you go back to Tableau Pulse and you're landing on this page and you're like, hey, where's the metric I just created? It's not here. So here's the thing.

The metrics you've just created you've not yet had a chance to follow said metrics. So if we go to browse metrics, you'll see that that metric is indeed there. If I click on it, I do actually get to see this.

And remember earlier on when I said that you create your definition and your first definition, you get a free metric with it. Essentially that first metric is the same as the definition without any segmentation. So what does that mean? Well, let's go to this metric and let's add some segmentation and you'll see how you can save additional metrics having defined them.

So we'll go ahead to this, we'll hit adjust, and then we can go ahead and start searching for specific things. So if I want to find all my videos that say Tableau Pulse, you'll see that it's able to go through and we can go ahead and just tick all of these and we'll hit OK. These are the five. So those five videos are specifically about Tableau Pulse and they're all from my channel.

There's nothing special there. Unfortunately. I'll come back to this point later, but if you've not done your data prep, it will show here. So the tags are not in the format I was expecting.

I was expecting them to be sort of separate items, but they're all just sort of everything I put into that space in YouTube. So it's not perfect. But nonetheless, we won't use that.

I can choose different contexts of time as well. This is super important. Depending on the context you have, you can choose week to day. And, you know, this changes the metric. So as soon as I hit this tick.

What that does is it saves an instance of a metric. And you'll see in the last week, nothing has happened. And a lot of you will see this the first time you use Tablet Pulse because your data has to be running to today's date. If you look at this, Tablet Pulse is always basing itself on today. And if your data doesn't have anything today, this is what you'll see.

However, if I go back and I adjust this metric, let's say we don't want to do week to date, let's do month to date, and we hit plus. then you'll see that we do get some information back and it stops right here okay and this is this is super useful because um i i spent about five minutes for the first time just trying to understand what was going on and i couldn't i figure it out and i realized oh it's because there's no so there's no there's no data in the context that i have so here we have the information these are just the videos related to tableau pulse so over the last month and there are about 22 subscribers who've come from videos relating to Tableau parts. Now we've done this a couple of times, we've created variations of this metrics a couple of times.

So let's go back and again when you hit back this time it takes you somewhere different to where I'd expect. Notice that rogue instance where we created a metric that didn't have anything in it, that was instantiated immediately. You didn't have really an option to save it or delete it and that's been created and the most recent one we created is also here so 22 here as well.

So There's a little bit of housekeeping you have to do. If you're just busy clicking these metrics and not sort of paying attention, you can come back here and find you've got three or four metrics you didn't intend to have. So you can obviously manage those by just going here, seeing the details.

And as soon as you go to the details, you can go back in there and actually go ahead. I thought you could delete them here, but actually that's wrong. What am I missing here?

Okay, I thought you could delete it here. Maybe I'm missing something. I could swear.

I found a way to delete a metric, but maybe I was deleting metric definitions. And so maybe this will come back to me, but. Hope hope you can delete these rogue ones because you saw how easy it was for me to create this null metric and they're kind Of frustrating as well because they don't need to get experience and if they're discoverable then hey You don't want people to be seeing these but nevertheless This is this is sort of the experience now Let me go ahead and hit follow on these two and if I go back to the tableau pass landing page by hitting that You'll see that those two metrics are created now land here on my landing page.

So We've got these nice metrics available to us here, and we can kind of just get using them. So if I go back into the subscribers, this is it. This is how it's working.

Now, at any point, if you want to change this, if you want to play around with this, if you click on these three dots at the top, you always get the option to edit the definition. And that takes you back to this experience. And you can obviously go back and change the insights. And when you do this, it changes the context each time. This is also a good place to go back to this insights tab and show you that now it's generated some context.

And what these really lend themselves to are the different types of insights that Tableau Pulse can generate. We've already been going for 20 minutes here, so I don't want to make this video longer by going into the different types of insights you can get. I'll do this in a separate video, but just be aware that there's a broad range of insight types and they generally map to these ones that you can see here. But in terms of how they play out, it probably helps to be able to see how those interactions work. So I'll come back to that a little later.

The other thing I'll also highlight as I sort of scroll up and down here. is that look, if you've not done your data prep upfront, this is just still not going to give you nice results. You can see here that the tags, the tags are just causing so much noise in here.

There's valuable information because I use these tags on videos where it makes sense, but they're just not being cleansed properly. What I would love to do is to have a way of being able to use this information and just pass this out so tablet can understand that although these are lists, actually all we care about is the items in each of these, in each of these. a list of values, arrays of values, as it were, if you're a programmer.

So it's just a little bit something sort of to bear in mind. If you're not doing a data prep up front, you're going to have to do it in Tableau Prep, Tableau Desktop in your data source, or do it further back somewhere more observable in something like DBT or in a data engineering operation that you're running. Okay.

The other thing I have to say about this, if I just go back and save this, we'll just save this as is, we haven't really changed anything, is... I would like the ability to be able to put what I would call a wildcard in here that updates as a data update. So at the moment, you can see the video title here. I can go ahead and type, you know, Tableau desktop and all the videos related to Tableau desktop come up. Now, the problem is, is, you know, when I when I deselect one, it deselects.

And if I hit exclude, it excludes all of them. So if I do exclude and then. I just sort of delete this.

You see that it says that all of them have been excluded. So there's no way for me to do like a wildcard search on the data set, if that makes sense. There's no way for me to say anything that mentions this specific term always added to this metric because then I think that makes metrics a little bit more meaningful and it makes these dropdowns actually represent what we can do already inside of Tableau today. So that would be one additional thing I'd love to see in the future.

But nonetheless, I'm not gonna create a new metric. I don't wanna create more noise. Right. The very final thing I know we've been going for some time, we're nearly 30 minutes in, is at this section here. This is where really the magic starts to happen.

If we spend a bit of time just working with this metric, you can see that obviously we've got the overview and the breakdown in here. And if we go to the breakdown, we actually get a little bit more of a detailed breakdown. And you can see this is a genuine reflection of my channel. The Tableau Desktop Crash Course is driving a good number of subscribers each month.

And if we go down the list, Other videos have a slightly smaller impact, but nonetheless, this is very representative of what I know and what works. If I select video tags, though, you can see the tags again are a bit noisy. And this makes us basically pointless because a large bunch don't have a value and the rest are just I mean, what can I really do with that?

OK, it's not much. It's too much information. I'll go back to the overview.

You can obviously hover over this and work with it, which is quite nice. And I like the fact that this is contextualized. I do need to get my data source to update a little bit.

So there's a little bit of an issue with my sort of data pipeline in the background. But here's the next really sort of exciting things. This section here is where the AI comes in.

So they call it GAI, so generative AI, right? These questions are part of sort of a system that Tableau's built where essentially the way that the platform works is the insight is actually generated from your raw data. That is just, you just think of it as maths being done on your data. And essentially those are facts. Those facts are then presented in order of preference, in order of sort of what's working and what's not.

And then once that's done. It's summarized by generative AI. And then what you get back is essentially these sentences.

And these sentences are a good way of helping the user go to the next question, understand what's going on. And so the computations that drive these questions have already been done in the background. But what these questions are is sort of tempting you to explore those journeys, take those journeys with your data. So if we go ahead and say, OK, which video title decreased the most? Which video title had the most negative impact on my subscriber count?

you can see here that it's actually what is Tableau. And this makes sense because the way you have to think of this metric is that the metric isn't about which video lost me subscribers. Remember, our metric was actually net subscribers. It's not subscribers lost.

It's not subscribers gained. It's net subscribers. So I could go ahead and recreate this with subscribers lost.

And this sentence would make more sense. But all it's saying is that I got 19 less subscribers this month compared to last month for this particular video. Okay.

And it gives us a nice sentence that actually breaks that down a little bit. And remember all the terminology we did before for singular versus plural. That's all in here.

That's all being used to kind of make this work really, really well. And as we click on these, notice every time I click on something here, it gets added just below here. Okay. So let's go ahead and see which video title had high subscribers.

So let's go ahead and hit that. Again, you get the Tableau Desktop Crash Course. You'd already seen that. And.

As you click on these, the metrics sort of go down. So I can kind of just click on these and you'll see that all the metrics sort of come through. And remember, some of these were some of the noisy ones we were seeing on the insights tab before. So that was already a preview of what you were going to see.

And it's essentially just enabling and disabling them behind the scenes. So it's a pretty good platform. And, you know, my data is pretty simple.

I'm just tracking one thing, subscribers. But in Superstore and in other data sets, you might have slightly richer context that you can work with. One thing I will say, if you're working with Superstore, make sure you shift the dates to the last day is actually today. Because if you don't do that, you'll see null for quite a lot of the Superstore data because it stops at a certain point in time depending on the tablet release.

So let's go back. That is pretty much the whole entire experience in a nutshell. That is how to use the platform.

What I will say is this, if I go back to the tablet past landing page, now that I'm here, you'll notice that this summary here at the top, being generated. So it kind of tries to pull out the most important things happening. So it says this month, there is a 5.9% decrease in subscribers based on this video.

So what is Tableau explaining under 10 minutes? So basically it's saying, hey, there's a 6% decrease in this one video compared to last month. However, there is a significant increase, 28.3% in overall subscribers compared to the same time last month.

So in broad brush terms, I'm doing well, but being specific, there's one video that's... got an impact. So I might choose to go and analyze that.

I might choose to go and do something else. Now, unlike other features in Tableau, these thumbs up and thumbs down help improve the system. Tableau is using these as prompts to try and understand what people are interested in and what they're not. So if I say that this is good, you can obviously send that feedback to Tableau.

I won't bother here. But what this will help you do is try and understand what's going on. Other things to bear in mind, you'll see this says it was last updated 12 hours ago, and that's because I'd already created this data set whilst doing a demo. So this sentence suggests a couple of things, and it's sort of a really intriguing fact about Tableau Pulse and how it's working behind the scenes.

12 hours ago, I'd just finished recording what was the third take of this video, right? And what's ended up happening is it somehow cashed... that data source and it's remembered that it's seen this this data source before likely because it's linked to my tableau cloud instance so rather than regenerating all the insights it actually found that it already generated them and it's simply serving them up from the cache even though you've watched me create these metrics for the first time and add the data source for the first time to tableau pulse whilst doing this so it does suggest a little bit of caching a little bit of what I would suggest sort of frequency in which it's going to be updating these metrics based on how often the data source is updated.

So if the data source isn't updated, I don't expect this to change, but if it's updating frequently, then I would expect tablet paths to hopefully pick up on this frequency. Anyway, these are small nuances to bear in mind as we start to get to know this feature a little bit more, but nonetheless, I think that is pretty much all I want to cover today. We've been going for a long time, 30 minutes.

It's a really long time for a video. Dude, thank you for watching this. If you've watched it all the way through, let me know what feedback you have about this video, about the feature below. I do know the Tablet product team do see the comments. So go ahead, let them know what you think.

Save me the sort of job of having to summarize it for them. But the other thing to bear in mind here is there's so much more to discover. So if you've discovered something, you find it super useful, if you've got some questions and you'd want to sort of find out, you know, how to execute that.

Let me know in the comments below. We'll try and see what we can do in the coming days. I need to spend a bit more time generating a bigger range of metrics and a bigger range of insights.

So I'm slowly working through building a bunch of datasets that are going to slowly update over time. And we're going to try and use Tableau Pulse to see how well it passes out some of that information. That's super important in this particular case, because I think this is a new feature it's going to have. a lot, a lot of sort of strange edges and rough edges that we need to sort of iron out. The last thing I'll say, though, is that at least on this release, now that it's public, there are a few features missing from Tablet Cloud that I would have expected to be in here.

Specifically, if you're paying for something like the data management add-on, I would have hoped to have seen more information about lineage. If I go to a metric, for example, I would really hope that once I'm here... I start to see a little bit of information relating to lineage, maybe some charts and dashboards that use the related metrics so that I can go off and see the same context inside of the Tableau cloud world.

Now, I do know that it's a deliberate choice by Tableau to make Tableau Pulse a separate experience, so it doesn't have to be encumbered by all the effort and all the sort of legacy that is Tableau cloud and Tableau server. But at the same time, I think it's a normal expectation, especially in the most recent years where Tableau and We've been really pushing the data management add-on to lots and lots of customers to really bring that value through to new platforms. Otherwise, it does sort of beg the question of, you know, when you subscribe to these things, how secure is your investment if they're not being pulled through to new features? You know, if you'd used Ask Data or Metrics in the past and you've spent the last three years finding a sweet spot where these work, great.

I do think Pulse is a better product than Metrics, definitely. But all the less, you know, the time you've invested in that. kind of you know doesn't really pay off here it's a completely different experience you have to reset your expectations you have to rebuild you the way it works the other final thing is that we will do a video on how to use this as an end user some of the feedback i get is that look a lot of my videos are great for authors but what about just end users who don't care about building these things i'm just going to come and use these metrics we will do a dedicated video on that just to make it easy for everyone to be able to share that as well okay we've been going for long enough And I really hope I haven't missed anything. That's sort of my biggest nightmare.

This is the fourth time I've recorded this. And so I think I've done it in a much more logical order this time around. So this is just, you know, an honest, honest experience.

Let me know what you think. Let me know if there's anything missing whatsoever. We can cover it later on this week. As ever, thanks for watching and I'll see you in the next video.

Transcript for:Understanding and Utilizing Tableau Pulse

Transcript for:
Understanding and Utilizing Tableau Pulse