1.2 Introduce the Power BI environment - Video Tutorials & Practice Problems

<v ->Okay.</v> So in this lesson, we're gonna introduce you to the Power BI environment. And we're first gonna start off by walking you through the power BI high level architecture. All right. So as you'll notice on the diagram, cutting right down the middle of it is a dotted line and that is meant to separate two key areas of our services. So below the dotted line is what we're gonna consider on-premise. So those are things that are installed within your wall. So for example, installed on your, a desktop or a server room, maybe in your organization. Those things are considered on premise. Above the dotted line we're considering to be cloud. Okay, so let's start first thing. So what we're going to do here inside of the Power BI desktop in the bottom left-hand corner of the screen, is we first want to work on connecting into data sources and ingesting them into the Power BI desktop. We're then gonna bring that data in go through some transformations and get it into a report ready state. We're gonna dive into more details on the whole process, but let's just consider those first two errors there. Getting data into the desktop and getting it into report ready state. And finally building some reports that we can use for consumption. Once that's complete, we want to go through a published process. So we're gonna take our work that we've done on the power BI desktop, and publish it into the power BI service that resides in the cloud. At this point in time, the work that you've published will be available through a mobile device and almost instantaneously, it will be available to you in power BI mobile. And if you have access to the power BI mobile app on your preferred mobile device, then you can access your content through there as well. Okay, so then next one is happening here from a high level architecture and we're not actually going to do this piece in this particular class because it's beyond the scope of it, is the setting up of a gateway. So the reason that we need to set that gateway up, is we somehow need a way to get our refresh data on a daily basis or whatever your schedule happens to be, from our sources on premise up into the cloud. So the gateway is essentially going to be that transportation highway that allows the Power BI service to connect back down into your on-premise data sources. And bring the new data into the service on your scheduled refresh basis. If you have data in the cloud, you actually don't need the data gateway. You can actually just connect directly into those cloud-based sources. So that's a really nice piece of your data residing in the cloud. And just for completeness of the diagram, we have that piece of infrastructure in the bottom right hand corner of the screen there, the Power BI report server. So if you actually want to do Power BI work and build things up, but never publish it in the cloud and take advantage of some of the features in Power BI, you can utilize the Power BI report server. We're not gonna cover that in this class it's beyond the scope of this. And yeah, so just want to make sure that you have a complete picture of the Power BI high-level architecture cause you may run into artifacts online as you're learning more about Power BI or refer to the Power BI report server. It's important just to understand where it fits. But we're gonna be doing all of our work exclusively in this class with the Power BI desktop and the Power BI service and then touching on the Power BI mobile as well. All right. So let's just talk about the Power BI end to end process flow here. So back in one of the previous sub lessons, we talked about the data analytics life cycle and how we go from a business question to ultimately satisfying the answer to that question. So what we're gonna do first is we're going to take advantage of the Power BI desktop. So we're going to get that installed on your machine so that you can go ahead and do some of the processes below here. So in the Power BI desktop we will work with the power query editor. We're gonna do some data modeling. We're gonna end up building some reporting. And ultimately when we're done those high-level processes, we're gonna take our work and publish it into the Power BI service and put our work into a workspace in that service. So that's a very high level process flow. Diving into a little bit more detail here as we talked about in the previous sub lesson, we first need to go in and find our data sources. So we're gonna make a connection to a data source. Once we find the source that's gonna answer our business question, and then we're gonna go ahead and extract that data from that data source. Once we bring it into the power query editor from an extract perspective, we're gonna go through a transformation step. So that's that little T right above the query editor. And we're gonna go through and transform data. We're gonna go ahead and introduce you to the M language that is inside the power query editor. Although largely a lot of the transformations that you would performing, you can do through wizards and configuration screen. So there's really no need at this point to dive into the language, but we introduce it to you just so you're aware of it's existence in Power BI and where it fits. Once we go through that step of transforming our data and getting it ready for reporting, we will then load that data over into the data model. Once our data is loaded into the data model and we have data that is almost ready for reporting, we're gonna go through a process of adding extra value to that data model. We're gonna build relationships between our tables. We're gonna perhaps add hierarchies to our data model which we'll do in this course. We will then go through and build some DAX expressions. So for example we're gonna take advantage of building some measures. Once we have our data model ready for reporting, then we're gonna go ahead to the report canvas and start doing some visualizations. And take those visualizations and craft stories. And hopefully stories that are compelling, easy to understand, and ultimately are gonna satisfy our business questions. And we actually want to make it look nice. So we're gonna go through some things around making your analytics look good. So that's visually appealing for your end users. Once we're done all this hard work, and everything to this point here is the bulk of the work inside of Power BI. So in the first two steps there of acquiring data through power query editor and putting the data model, that typically is about 70 to 80% of the work in any analytics endeavor. Once you have data in a report ready state, reporting actually isn't as difficult as one might think. For a lot of years, the data acquisition reporting all got lumped into one process. So there was a lot of, you know, talk around how difficult reporting was. But really if you separate the two, most of the hard work was back in the actual acquisition and cleansing the data. Once you actually got data into report ready state, reporting typically isn't that difficult. Now I'm not trying to make it seem simple. It certainly is made easier if you actually have data in a much more cleansed and report ready state. Once we have built stuff on the report canvas, we will then publish our work into the Power BI service. Because that is where people are gonna go ahead and consume our data. We will work on sharing our data out. We're gonna show you some great security features that are embedded into Power BI so we can better secure our data than we have in other reporting tools. And we're gonna just briefly touch on some governance features that are available in Power BI as well. So this, at a very high level, is the Power BI end-to-end process flow that we're gonna use that maps back to the previous sub lesson where we talked about the data analytics process flow. How we're gonna connect to sources and ultimately deliver the visualizations and answers to business questions to our business users so they can consume it. And once again, with this, you'll find this is a highly iterative process. This is illustrated as being linear but there's a lot of back and forth in this process as we discover new things. Right. That brings us to the end of the sub lesson.