This video helps you understand the basics of exploring data models inside the Looker platform.
- [Instructor] Now that I have my test environment set up, I'm going to dive in, and show you how we can actually explore some of the test data that's loaded. So first, I'm going to punch in the URL for my Looker instance. Now, there will be a message here about it not being private. That's because there's no SSL certificate for this new virtual environment we just created. So, in Chrome, you'll get this message. In other browsers, you may see different ones. But, you should have some options to proceed, to go to that actual site.
So, depending on your browser, you'll see a different looking page, but you should have an option to get there. Now, here is where we can actually log into Looker. I'm going to hide my URL bar, because it's not needed any more. And my login was stevejobs, and they sent me a generated password, which has a lot of characters. So, I'll just copy and paste that from my email. I'll log in. And when we get here, we have this Test Drive, we have all these good links here.
So, let's start by exploring some data. Now, this tutorial here is really well built out. And, I'm going to go through this step by step with you. But for a reference later, you can go to their learning page, and find all this information. So back here in the environment, I want to go up to Explore. And you can see that I have several of these already built out. So, I'm going to click on the first one Orders, Items and Users. So what we have here is in Explore, it's a unit that they use to define, basically, a query or a query result set.
So, let's first take a look and see if we can't figure out how many orders we have over time. So, on the left I have, essentially the different tables that are being used. And what I can do is just click on one of 'em. And I can see Orders, I can see Created Date. I can click on that, and I can see all the different things here. Let's, maybe, go up to Week, click on that, and you can see that it added it to my Results here. Now, I don't have any results showing, because I need to click Run. But, before I do that, let's just take a look at what happened. I added this Week level of my Created Date field, and it generated some SQL for me.
You can see there's actually quite a bit of complex SQL, that goes in to just calculating the week of when the order was created. And this is one of the powerful things about Looker, is that it did all this for me, based on the lookml, which we'll take a look at here in a second. Okay, so I now have my order by week, and then, maybe just order count. Cool, so I have two columns there, and I'm going to click Run, and there you have my orders by week. Again, I could take a look at the SQL here, and find that essentially, it had the week calculation to begin with, then it had the count distinct of orders.
So, this was all generated for me automatically. I didn't have to write a single line of code, to get this result set. So all we're doing is taking a look at the results right now in table format, but I also can do a visualization, and apply filters. Let's add another field here. So, let's say I want to see the orders by week by category. If I just click on Category, you can see that it added it there. It doesn't have any values yet, because I haven't run my query. But, if I go to my SQL again, you'll see that it actually did two different joins here, to get the category of my product.
So again, all of this is happening behind the scenes. I don't have to know any of that, or understand any of it. I just go to my Results, click the fields I want, then click Run. So there you go. Now, I have a message here about the Row Limit being reached. And that's because I have something set up over here, with the Row Limit. And that's because, in the web browser, I don't want to list 10 million rows of data. So, Looker is smart enough to try to control that, so I still have a good user experience, without having to, you know, bog down my browser, and potentially crash it.
We all have those stories, and we remember of when you punch something into Excel, and it has to recalculate, and it just kills your whole machine. So, Looker helps save you from that by doing things like Row Limits, and controlling the amount of memory being used on your computer. So similarly, I could add different measures here. Now notice that Dimensions, these are the categories of things. Measures are the numerical things, the numbers, the things that we aggregate. I like to think of these Dimensions as the context of our analysis.
You can see all of them broken out here. And Measure is the subject of our analysis. So, in this case, we're looking at Orders. So Orders is really the subject of this explore, of this view. And the context is by week, and by category. So these are different ways of talking about your data. And these terms are used pretty ubiquitously throughout all other business intelligence and analytics applications. So, if you're familiar with dimension tables, and fact tables and measures, and all those other terms that we use in business intelligence and data warehousing, it's going to translate really well into Looker.
So, it makes a lot of sense if your familiar and you have a SQL background.
- What's Looker?
- Taking Looker for a test drive
- Exploring data in Looker
- Creating expressions
- Visualizing data in Looker
- Building dashboards
- Scheduling data deliveries and alerting