Summary - Case Study

In this session, you learned about the problem statement that we will be solving in this case study. The business problem is about a telecom company that is concerned about losing its existing customers and wants to come up with a solution so that it does not need to worry about customers leaving.

To solve this problem, you learned about two key metrics that you will be analyzing in this case study. They are:

1. Customer churn, which can be defined formally as the percentage of customers who have discontinued their subscription to a service in a given period of time, and
2. Customer lifetime value (CLV), which is the net profit associated with a customer for a company over a fixed period of time.

Next in this session, you learned about a new tool called SQLite, which comes readily installed with Python and is generally the go-to library when we want to run SQL queries directly on Python. 

The differences between MySQL and SQLite are summarized in this image.

You also learned why it is important for you to be able to use SQL on Python.

Further in the session, you learned how to use SQLite in Python and extract the data in a database in the form of a Pandas dataframe. You also learned how to import different csv files into a database and print the column names and the schema of the tables in a database.

This brings us to the end of the first session of this case study. In the next session, Favio will actually start the churn use case. You will see all the concepts taught in this session being applied in the next session.