seriouswill / sql-for-data-processing-and-analysis

SQL for Data Processing and Analysis

Coaching this? Read the coach guidance here.

Learning objectives

In this module your learning objectives are:

• Learn to efficiently analyse data stored in a relational application database using SQL
• Learn to sanity check and debug SQL queries
• Learn to build analytics dashboards using Jupyter Notebooks and SQL
• Learn to plan and design a data analysis project based on a set of requirements

Introduction

To Software Developers, SQL is a language that allows an application to interact with a relational database. Often their use of SQL is indirect - there are a lot of tools that abstract away the SQL leaving Developers to use the methods or functions of their favourite programming language.

To Analysts, SQL is a language can be used to ask really interesting questions of a dataset. Analysts in government, for example, might be asked to provide some statistics about how crime rates have changed over time or from area to area. Assuming they have some related data in a relational database, they can use SQL to find the answers.

To Data Engineers, SQL is a language that can do both of these things :)

In this module, you'll start by thinking as an analyst and as you progress through the initial stages you'll learn how to ask more and more interesting questions of the data you're working with.

At the end of the module, you'll think as a data engineer once again as you take on the challenge of using SQL to build a dashboard.

Sequence

Work through each of these phases in sequence.

Some of these challenges include submissions in which you share some of your for feedback. These are tagged with a 📡.

Phase Zero: Introduction

1. Introduction to the module
2. Markdown Guide

Phase One: SQL Foundations

Revisit the basics of SQL and learn a few more tricks.

1. Set up your SQL database
2. Set up your SQL development environment
3. Revisit the basics of SQL
4. Limit the length of query result sets
5. Order query result sets
6. More ways of filtering query results
7. Perform calculations on numeric data in SQL

Phase Two: Complex data manipulation in SQL

Learn to answer increasingly complex questions about data using SQL.

1. Summarise data using SQL Aggregate functions 📡
2. Interlude: Debugging SQL Queries
3. Combine data from multiple tables using SQL Joins
4. SQL Subqueries: Use the results of one query as an input to another query
5. Interlude: Debugging Advanced SQL Queries 📡

Phase Three: Business scenario

Build a product metrics dashboard for Stack Overflow 📡

---

How was this resource?
😫 😕 😐 🙂 😀
Click an emoji to tell us.