ERD Creation and RDBMS Validation Using SQlite and Python

In the previous segment, Favio created the customer churn database using Python. Now, in order to represent our database, Favio will now create the ERD for this database. For this, we will be using a new tool, called dbdiagram.io.

In the forthcoming video, Favio will show you how to create the ERD. Let us go ahead and watch the video.

So, as you just saw, building the ERD is very simple using the dbdiagram tool.

You can access this tool at this link:
https://dbdiagram.io/d.

Moving on, in the next video, Favio will continue creating the ERD for this database. Let us go ahead and watch the video.

So, in the video, Favio created the ERD, which you can view by clicking on the link below.

So, in the video, you saw that our database satisfies all normalization up to the third normal form. You also learned that we can now export our ERD either into an image or directly into MySQL.

So, with our database now prepared, we can now begin our analysis of customer churn. In the next segment, Favio will perform a basic data exploration directly on the SQLite browser.

Now that the ERD is ready, you can see that our database is a lot more structured as compared with having a number of csv files. Before we move ahead with the analysis, we must also check whether our database is an RDBMS by checking its properties and normalization rules. Favio will discuss this in the next video.