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SQL for Data Analytics

SQL for Data Analytics - Third Edition

By : Jun Shan, Matt Goldwasser , Upom Malik , Benjamin Johnston
4.8 (53)
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SQL for Data Analytics

SQL for Data Analytics

4.8 (53)
By: Jun Shan, Matt Goldwasser , Upom Malik , Benjamin Johnston

Overview of this book

Every day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience. You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.
Table of Contents (11 chapters)
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9
9. Using SQL to Uncover the Truth: A Case Study

Cleaning Data

Often, the raw data presented in a query output may not be in the desired form. You may want to remove values, substitute values, or map values to other values. To accomplish these tasks, SQL provides a wide variety of statements and functions. Functions are keywords that take in inputs (such as a column or a scalar value) and process those inputs into some sort of output. You will learn about some useful functions for data transformation and cleaning in the following sections.

The CASE WHEN Function

CASE WHEN is a function that allows a query to map various values in a column to other values. The general format of a CASE WHEN statement is as follows:

CASE 
  WHEN condition1 THEN value1
  WHEN condition2 THEN value2
  …
  WHEN conditionX THEN valueX
  ELSE else_value 
END;

Here, condition1 and condition2, through conditionX, are Boolean conditions; value1 and value2, through valueX, are values to map...

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