Now let's work on a real world example, which is NBA statistics. So this is more of the basketball side. And we're going to be working on this side stat that nba.com. So don't worry, as we won't be using all of this numbers. So even if you do not know about basketball, and what are the statistics involve, you will still be able to see the power of Power BI, okay? Because what I'll be doing is we'll be just picking a couple of stats in here and I'll be walking you through on what each means, okay, so that you can gain an appreciation of how it's related, and what are we doing with this data?

Okay, so the goal here is to show you how do we mash multiple data sources, because from here, what we'll be doing is we'll be getting stats and numbers from three different sources. Okay. So we're doing this live as well. So which means we're working on a live website, we're getting the data and then we're getting it straight from online source. So that's pretty cool, actually. So I'm pretty excited.

And let's go over to different data sources that we'll be working with. Okay. So the first one is more of team stats. So this are the traditional stats in here. And what I'm doing is I'm getting it from the year 2017 to 2018. So that's a date in the past.

So we have full numbers from a regular season. So this is just a regular season. We're in each, like team battles against other teams. Okay, so they play against teams over here. And you can see here on the left side is we have a list of all of the teams, the NBA teams over here, right? And then we have a couple of statistics.

So we have games played, how many games did they play? How many wins? How many losses? What is the wind person page, okay, so it's just more wins divided by number of games played, then the number of minutes and then the points Okay, that they scored. And for the rest So the statistics, we won't need this anymore. Okay, so we're just after the point scored for each team over here.

Okay? So that's for the traditional team stats. Now we're going over to team defense. Okay, so for team defense, what we want to see so same thing you could see all of the teams listed out over here. We have the games play, we have the winds, we have the losses, okay, what we're after is the defense or the defensive rating over here. So it's just a score to say how good the defense team is.

Okay, so that's what we're after. Okay. So for the rest, we'll be removing the SSL later, we won't need the rest of the data. Okay. So that's for team defense. Now, let's move on to the third one.

Teams clutch, okay, team clutch that so when we say clutch, okay, so clutch. It's just a fancy way of defining the last five minutes of the game. And the difference between the scores of the competing teams is from points are less. So in other words, it's just simply put, it's a competitive game. It's a game that's very close, and you're not sure on what will happen in the final few minutes, because you don't know who's gonna win because the score is very close. Okay, so that's actually the most exciting type of games to watch, because you'll be on the edge of your seats while you're watching on who's going to be winning until the very last second.

Okay, so over here, if you could see here, that same thing, right, you have all of the temps listed. And if you notice a while ago, if I just move back to the first list, you could see that it's 82 games at two games for all of the teams over here, right? Because in one season, or in one year, you could think of it that way. Is each team plays 82 games. That's a lot. Yeah.

And if we move over to the clutch, not all of the games are clutch games, or our close games, right? Some of them are close. Some of them the scores are pretty far from each other. Okay, so which means each team would have different experiences. And they have different clutch games or number of close games played, right? So you can see that Cleveland, for example, has played in more close games as compared to Houston.

Okay. Over here, what we're after is the number of clutch games played, okay for each team. And we could just keep a couple of columns in this data and then the rest will just remove them as well. Okay, once we start working with the data, okay, so now we have all of the three data sources explained. Right. So what I'll do right now is just show you on what is the solution that we're after.

So what we're after is, so I'll just go over here quickly, and go to our query. So what we want to happen right now is we want to load all of these three sets of data into our Power BI solution. Okay, so once we have it here, we'll just be doing some couple of transformations to clean our data. Okay, and then afterwards once we have that ready, so we have here stats team defense template, right? Once we have that ready, we'll be loading that into our data model, right so that we can link them together and have them to be related with one another. Okay, so we can establish the relationships between this tree entities.

And once we're done, we're going to be creating our visualizations. And this is the fun part because you can now see the cool data. Okay, on what we have here, don't worry, I'll be walking through you over here each step, okay, step by step for each one of how we created all of this cool visualizations over here. Okay, so look forward to it. And now we will get started with loading our data into Power BI Desktop.