Transcript
I am back with the final video in the Do More with Qlik data product series, ultimately ending up to this point where we're going to now create a data product. In this case here, I have a brand new space with orders, customers, products, and line items data sets. They have all been explored and some of them have had some data validation rules applied to them, etc. So now what we're going to do is create the data product. And as you might remember from the first video, a data product is nothing more than a collection of those data sets with all of the additional metadata for data quality and data validation, as well as information about the health of the data through the Qlik trust score. And you can refer back to the other videos to see all of those pieces in more detail. What we're going to do now is just create the data product with these data sets. So I'm in my catalog, I'm in my space, I'm going to select create data product, and we're going to give it a name. We're going to put it in the space that we're working in. In this case, I'm working in a new space called video data product. So we're in the video data product space. And we're just going to call this one order retail analysis and click continue. So now we can add a description. We could also select the data sets. So in this case, I select add data sets. And in the space we're going to choose is the same one that we are currently in right now. And I'm going to choose orders, customers, products, and line items, and click confirm. If I want, I could add documentation, I could attach these to business glossaries. I can even make these accessible through API endpoints. And then also assign key contacts. So here, I'll just add myself. And then click Save. That is all you need to do. So at this point, we have our data product. You can go through the various tabs here to see additional content and context. But at this point, we're just going to activate it. Now when you activate a data product, you're basically making it available within a managed space. So you have managed space available. If you are not familiar with managed spaces, managed spaces are the location where information is consumed by your business users and your analysts, not an area for development. That's what a shared space is. So I have one here called sales managed. And I can click generate description. And based off of the content that's in the data product, the AI generator will develop a description that you can use. And then we could also put some feedback here if you wish. But we're not going to do any of that right now. And just click activate. So that's it. It's now activated. So as my account, which is logged in as Mike Tirallo, if I go under analytics, you'll see something called data marketplace. If I click data marketplace, you can now see the order retail analysis data product. So what we're going to do now is I'm just going to switch users. And I just have another browser session open with a different user account. And you're going to see how they will view this data product and how they can use it. So to do that, I actually just have a Firefox session open. And you can see they have access to the catalog. And you can see there is the order retail analysis. And you can see there's the data product. This is the view through the catalog. I'm logged in as John Doe in this particular instance. But if they go to data marketplace, they basically have one location to browse and discover and explore data products that can be used, for example, within a data flow, a table recipe, an application, or even a script if they want to take it to that level. So you can search for different data products. You can click each one to explore. Notice here's the order retail analysis one we just created. I'll click that. You can see the click trust score is showing a very healthy score, knowing that this is some good data that we can use for our analysis. And then again, the different tabs and content that they can look at. At this point, they want to use the data product. So they can use it within an application, table recipe, a data flow, or a script. And if there were endpoints set up, you could use that as well. In this case, to keep it simple, we're just going to choose application. And I'm going to create this application in my personal space. And we are just going to call it order retail analysis application and click Continue. So this is basically going to create a ClickSense app using those four data sets. But you can see it's all contained for you. But you have an option basically to go through the details and look at the different pieces of information, et cetera, if you want to. But at this time, we're just going to click Next. Once again, you have the ability to select the different field elements you may want. But again, just going to jump into load into application. Now at this time, what it does is it brings you into the data manager. Some of this experience will change over time as we start to release new features. But at this time of the recording of this video, it brings you into data manager. And it'll look at the different keys within the tables. It'll make recommendations for associations. So here I can preview. And then if I click the center dot, you can see it's linking products and line items together on product ID. It's linking line items and orders on order ID. And it's linking customers to orders on customer ID. That's exactly what we want. So we're going to click Apply All and then Load Data. Now if your keys are a little bit different, technically data manager can set them up. You can do manual associations as well. But for this video, we're just jumping into so you can get an example of how it works. So here we can click Go to Sheet. Now I'm going to enable this for ClickAnswers. So I'm going to actually go into Settings of the app, Capabilities, and we're going to turn on the switch available in ClickAnswers. And this will take a few moments basically to prepare the data. As you know, ClickAnswers is your AI assistant. And not only can it work with structured data, but it also can work with unstructured data. Originally, when we set up ClickAnswers, we had a knowledge base where you can load unstructured data into it and ask questions and create prompts to explore that data. And as you may know, you can do that now with ClickSense apps. Okay, the indexing is complete. We can click Done. So technically, without even having to create a KPI or chart, I can jump right into ClickAnswers. Let's just go into fast mode. How many orders are there? Okay, we have 4,000 orders. Show me an order count by payment method. Okay, so we have order count by payment method, cash, gift card, debit card, credit card, and PayPal. And then we have 80 orders with no payment method. But basically, just to give you an idea of using that information that we set up with in the data product is now available for analysis. So at this point, I can take this actual chart and we can put it in our new existing sheet and to existing sheet. And there we go. Alrighty, so that is it for data products. I really am interested in your feedback. And please ask questions where this video is posted. I'm really curious to know what you think about what I've showed you. And if there's anything I can do to be of assistance along the way, please feel free to reach out. I'll do my best to accommodate. Thank you guys. Have a good one. And I'll see you on the next video.
