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SQL for Data Analytics

SQL for Data Analytics - Fourth Edition

By : Jun Shan, Benjamin Johnston, Haibin Li, Matt Goldwasser, Upom Malik
4.5 (2)
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SQL for Data Analytics

SQL for Data Analytics

4.5 (2)
By: Jun Shan, Benjamin Johnston, Haibin Li, Matt Goldwasser, Upom Malik

Overview of this book

SQL remains one of the most essential tools for modern data analysis and mastering it can set you apart in a competitive data landscape. This book helps you go beyond basic query writing to develop a deep, practical understanding of how SQL powers real-world decision-making. SQL for Data Analytics, Fourth Edition, is for anyone who wants to go beyond basic SQL syntax and confidently analyze real-world data. Whether you're trying to make sense of production data for the first time or upgrading your analytics toolkit, this book gives you the skills to turn data into actionable outcomes. You'll start by creating and managing structured databases before advancing to data retrieval, transformation, and summarization. From there, you’ll take on more complex tasks such as window functions, statistical operations, and analyzing geospatial, time-series, and text data. With hands-on exercises, case studies, and detailed guidance throughout, this book prepares you to apply SQL in everyday business contexts, whether you're cleaning data, building dashboards, or presenting findings to stakeholders. By the end, you'll have a powerful SQL toolkit that translates directly to the work analysts do every day. *Email sign-up and proof of purchase required
Table of Contents (21 chapters)
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Lock Free Chapter
1
Part 1: Data Management Systems
6
Part 2: Data Presentation and Manipulation
12
Part 3: Advanced Topics on Analytics
19
Other Books You May Enjoy
20
Index

Summary

This chapter focused on presenting data using the SELECT statement. It began with an introduction to reading data from existing tables using the simplest form of the SELECT statement. It then explained how to specify a list of columns, provide an alias, limit the result size, sort results for displaying, and select distinct values. The WHERE clause was then introduced to filter query results based on specific conditions, including using Boolean operators (=, >, >=, <, <=, <>, and !=) and logical operators (AND/OR/NOT), IN/NOT IN, and IS NULL/IS NOT NULL. The query logic for handling NULL values was also explained. With these skills, you will be able to query any table with desired conditions and selections to gain insights into the data.

Often, you will need to transform the data so that it is easier to understand. For example, you may want to get the current date, or to filter string fields based on the combination of words. This requires further data...

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Tech Concepts
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Programming languages
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SQL for Data Analytics
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