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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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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

Using SELECT expressions

So far, you have used the most basic SELECT query of this pattern:

SELECT * FROM <table_name>;

This query pulls all rows from a single table. For each row, all columns are displayed. This can be used to check what data exists in the table. However, selecting all columns blindly is usually not necessary and can cause significant performance issues. Many times, you can specify the list of columns by replacing the * sign with a list of column names, such as the following:

SELECT product_id, model, base_msrp FROM products;

This will return the product_id, model, and base_msrp information of all the products in this table. You can arrange the columns in any order, regardless of the order in the table definition. PostgreSQL will display the columns based on the order in the SELECT statement:

product_id |         model         | base_msrp
-------...
CONTINUE READING
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SQL for Data Analytics
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