Book Image

SQL Query Design Patterns and Best Practices

By : Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang
5 (1)
Book Image

SQL Query Design Patterns and Best Practices

5 (1)
By: Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi 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)
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 learned how to use the PIVOT and UNPIVOT operators and how we can use them in our advanced query techniques by transforming rows into columns or vice versa. We looked at a few examples and also learned how to dynamically construct column names that are used in pivoting operations. Both of these operators are very powerful and are a very good and clean replacement for the lengthy CASE statement we studied in Chapter 4.

The PIVOT option is used a lot for reporting purposes and analyzing data in different formats and UNPIVOT is more for denormalizing datasets and storing them in SQL tables.

Next, we looked at the new way of storing hierarchical data, using the hierarchyid data type. We walked through a very typical use case of storing organization hierarchy data with examples.

In the next chapter, we will move our focus onto the security aspects of SQL queries and the things we need to take care of while querying data from a database, along with how...