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SQL Query Design Patterns and Best Practices

You're reading from  SQL Query Design Patterns and Best Practices

Product type Book
Published in Mar 2023
Publisher Packt
ISBN-13 9781837633289
Pages 270 pages
Edition 1st Edition
Languages
Authors (6):
Steve Hughes Steve Hughes
Profile icon Steve Hughes
Dennis Neer Dennis Neer
Profile icon Dennis Neer
Dr. Ram Babu Singh Dr. Ram Babu Singh
Profile icon Dr. Ram Babu Singh
Shabbir H. Mala Shabbir H. Mala
Profile icon Shabbir H. Mala
Leslie Andrews Leslie Andrews
Profile icon Leslie Andrews
Chi Zhang Chi Zhang
Profile icon Chi Zhang
View More author details

Table of Contents (21) Chapters

Preface 1. Part 1: Refining Your Queries to Get the Results You Need
2. Chapter 1: Reducing Rows and Columns in Your Result Sets 3. Chapter 2: Efficiently Aggregating Data 4. Chapter 3: Formatting Your Results for Easier Consumption 5. Chapter 4: Manipulating Data Results Using Conditional SQL 6. Part 2: Solving Complex Business and Data Problems in Your Queries
7. Chapter 5: Using Common Table Expressions 8. Chapter 6: Analyze Your Data Using Window Functions 9. Chapter 7: Reshaping Data with Advanced Techniques 10. Chapter 8: Impact of SQL Server Security on Query Results 11. Part 3: Optimizing Your Queries to Improve Performance
12. Chapter 9: Understanding Query Plans 13. Chapter 10: Understanding the Impact of Indexes on Query Design 14. Part 4: Working with Your Data on the Modern Data Platform
15. Chapter 11: Handling JSON Data in SQL Server 16. Chapter 12: Integrating File Data and Data Lake Content with SQL 17. Chapter 13: Organizing and Sharing Your Queries with Jupyter Notebooks 18. Index 19. Other Books You May Enjoy Appendix: Preparing Your Environment

Manipulating Data Results Using Conditional SQL

In previous chapters, we learned how to use the WHERE clause and a series of functions to filter down and format the data results. Now, what if we must give certain field values a new definition to make them more understandable? For example, the state names in the database were stored in abbreviations, however, the reports the data serve are meant to serve international stakeholders. So then, how can we present IL as Illinois and CA as California without having to add a column into the database taking up permanent storage space? Or perhaps, for better grouping purposes, we want to be able to provide the report users with a country-level sales revenue number instead of just state-level details. This is when we head into the conditional query world, by defining the grouping rules at query runtime.

In this chapter, we will learn about when and how to use the CASE, COALESCE, and ISNULL statements, noting the advantages and disadvantages...

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