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SQL Query Design Patterns and Best Practices

SQL Query Design Patterns and Best Practices

By : Steve Hughes, Steven Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang, Neer, Ram Babu Singh, Shabbir Mala, Andrews, Zhang
4.7 (11)
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SQL Query Design Patterns and Best Practices

SQL Query Design Patterns and Best Practices

4.7 (11)
By: Steve Hughes, Steven Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang, Neer, Ram Babu Singh, Shabbir Mala, Andrews, Zhang

Overview of this book

SQL has been the de facto standard when interacting with databases for decades and shows no signs of going away. Through the years, report developers or data wranglers have had to learn SQL on the fly to meet the business needs, so if you are someone who needs to write queries, SQL Query Design and Pattern Best Practices is for you. This book will guide you through making efficient SQL queries by reducing set sizes for effective results. You’ll learn how to format your results to make them easier to consume at their destination. From there, the book will take you through solving complex business problems using more advanced techniques, such as common table expressions and window functions, and advance to uncovering issues resulting from security in the underlying dataset. Armed with this knowledge, you’ll have a foundation for building queries and be ready to shift focus to using tools, such as query plans and indexes, to optimize those queries. The book will go over the modern data estate, which includes data lakes and JSON data, and wrap up with a brief on how to use Jupyter notebooks in your SQL journey. By the end of this SQL book, you’ll be able to make efficient SQL queries that will improve your report writing and the overall SQL experience.
Table of Contents (21 chapters)
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1
Part 1: Refining Your Queries to Get the Results You Need
6
Part 2: Solving Complex Business and Data Problems in Your Queries
11
Part 3: Optimizing Your Queries to Improve Performance
14
Part 4: Working with Your Data on the Modern Data Platform

Summary

In this chapter, we discussed how to determine what data you need in your result set to meet your analysis needs.

We started with some simple queries to identify what table we needed to get the data we needed, and then we queried the table to get a sample of data that was contained in it. Next, we created a query that would create a result set that met the needs of the request and showed how it could be turned into a view that makes the query easily reusable. We then wrapped up the chapter by showing how there may be a need to get data that is not available because it was filtered out.

In the next chapter, we will expand upon this knowledge to look at how to efficiently aggregate the data so that your queries will run more efficiently.

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