Exercise files - Power BI Tutorial

- [Narrator] We build Power BI models for sharing and scaling them across organizations. We can do so through server and cloud accounts like those available through the Power BI service and the pro and premium options. These options require a business email account and a monthly subscription service to access and share Power BI models. Even though these accounts are the end destination for many Power BI models, we're not going to use the service accounts directly in this course. You also don't need a Power BI account to follow along with this course. Instead, we're going to build the models in Power BI Desktop. You'll want to download it for free from the Microsoft website to your own computer if you haven't already. Updates to the desktop version come out once a month. You want to choose the version of Power BI Desktop that works with your own computer. My recommendation for building Power BI models in general is to create them in the desktop version then publish them to whatever shared account you're using when you're ready to do so. We're going to be getting the data that we use for this course from the Federal Reserve of St. Louis Economic Data to model loan calculations with mortgage interest rates. The FRED website is a great resource for free publicly available data. If you enjoy working with the data in this course, I recommend checking out the many other data sets available on this website. It also has an API to set up direct connections. I stored the data for this course project in a GitHub account specifically for this course. Power BI Desktop already connects to both of the mortgage rate data files for the course project, as well as the crop data file for the challenge. The data sources are also available in the data sources folder in the exercise files. I'm going to copy the link to the folder on my own computer. If you'd like to use the data source files in this folder on your own computer, you'll want to copy the link from your own computer as it will likely be different than the one I'm using. Each video in this course that directly uses the exercise files has a start and end state folder. If you'd like to update a Power BI Desktop files so it points to the data source folder instead of the GitHub account, you'll want to do this by adjusting the first step for the source of each data table connection in Power Query. Next, we'll want to remove the web.content step, which is a function, and the formula bar so we just have the code for csv.document. And in this case it's going to be the Mortgage15US. We'll then paste the folder path of the exercise files data source folder into this spot. We want to make sure that we keep the file name as well. You can set up these entire queries by hand, but this approach is a bit quicker. We also want to make sure all the slashes are facing in the same direction. So we'll change that final forward slash to a back slash. Once we update the folder path and the source step for the query, we see it updates the rest of the query within Power Query with the same result we saw before. We can then repeat it for the other queries as well. It's important to note that you don't have to even update this query because it automatically connects to the file in GitHub, but this is an alternative option for setting up the exercise files if you don't want to use the GitHub account. But I do recommend that you use the connected file that's already set up to GitHub to save some steps along the way.