Introduction to Analyzing Churn and LTV Using SQL and Python

The previous session helped you understand the problem statement and the business objectives in this case study. You also learned that we will be using SQLite, Python, and Tableau to perform the case study.

Further, you learned how to work with SQLite on Python with the help of the SQLite library and were given a basic introduction to the Pandas library, which we will be using to run more complex analysis on Python.

Before we get started with the case study, in the forthcoming video, Favio will quickly recall the data that we have at hand. Let us go ahead and watch the video.

You can download the slides, data and the codes used by Favio in this session from the link below.

In the next segment, we will start with the case study.
 

Guidelines for in-module questions

The in-video and in-content questions in this module are not graded. Note that graded questions are provided in a separate session titled “Graded Questions” at the end of this module.

People you will hear from in this module

Adjunct Faculty

Favio Vázquez
Data Scientist, H2O.ai

Favio is a computer engineer with an MSc in physics. He is working as a data scientist at H2O.ai, where he develops data-science-based solutions and applications using Python. He is also the founder of and the chief data scientist at Closter, a data science and educational company. Favio loves teaching and has taught at University of Berkeley, Dartmouth, Wharton, and Columbia University.