Book Image

SQL for Data Analytics

By : Upom Malik, Matt Goldwasser, Benjamin Johnston
3 (1)
Book Image

SQL for Data Analytics

3 (1)
By: Upom Malik, Matt Goldwasser, Benjamin Johnston

Overview of this book

Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don't know how to use it to gain the most effective business insights from data, this book is for you. SQL for Data Analytics helps you build the skills to move beyond basic SQL and instead learn to spot patterns and explain the logic hidden in data. You'll discover how to explore and understand data by identifying trends and unlocking deeper insights. You'll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you'll learn how to increase your productivity with the help of profiling and automation. By the end of this book, you'll be able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of an analytics professional. Please note: if you are having difficulty loading the sample datasets, there are new instructions uploaded to the GitHub repository. The link to the GitHub repository can be found in the book's preface.
Table of Contents (11 chapters)
9. Using SQL to Uncover the Truth – a Case Study

Reading Tables: The SELECT Query

The most common operation in a database is reading data from a database. This is almost exclusively done through the use of the SELECT keyword.

Basic Anatomy and Working of a SELECT Query

Generally speaking, a query can be broken down into five parts:

  • Operation: The first part of a query describes what is going to be done. In this case, this is the word SELECT, followed by the names of columns combined with functions.
  • Data: The next part of the query is the data, which is the FROM keyword followed by one or more tables connected together with reserved keywords indicating what data should be scanned for filtering, selection, and calculation.
  • Conditional: A part of the query that filters the data to only rows that meet a condition usually indicated with WHERE.
  • Grouping: A special clause that takes the rows of a data source, assembles them together using a key created by a GROUP BY clause, and then calculates a value using...