Introduction to the Extract, Transform and Load (ETL) Process

Description

This session introduces Extract, Transform, and Load (ETL) as a framework for acquiring, preparing, and organizing data for analysis. ETL is important because real-world data rarely arrive in a form that can be analyzed directly, making data preparation a fundamental component of the analytical process.

Motivation

How do we turn raw data into usable data?

Review

The prior session considered how analytics can be used to address accounting and business questions. This session begins developing the technical process required to obtain and prepare the data needed to answer those questions. This session will produce a roadmap for the significant ETL process focused module that continues through class 8.

Preparation

• There is no required preparation for this class.

Class plan

• We will briefly review class 1, focusing on developing the analytical mindset.
• We will introduce the roadmap for the ETL module using a set of in-class activities and demonstrations.
• We conclude this class making sure that the core ETL concepts are sound using a quiz-styled review facilitated by pollEverywhere.

Team format

discussion

Tools

• git commands to extract data from a github repository

Concepts

• data extraction