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.

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Spis treści

SQL Query Design Patterns and Best Practices. A practical guide to writing readable and maintainable SQL queries using its design patterns eBook -- spis treści

• 1. Reducing Rows and Columns in Your Result Sets
• 2. Efficiently Aggregating Data in Your Results
• 3. Formatting Your Results for Easier Consumption
• 4. Manipulating Your Data Results Using Conditional SQL
• 5. Using Common Table Expressions
• 6. Analyze Your Data Using Window Functions
• 7. Reshaping Your Data with Advanced Techniques
• 8. Impact of SQL Security on Query Results
• 9. Understanding Query Plans
• 10. Understanding the Impact of Indexes on Your Query Design
• 11. Handling JSON Data in SQL Server
• 12. Integrating File Data and Data Lake Content with SQL
• 13. Organizing and Sharing Your Queries with Jupyter Notebooks
• 14. Appendix – Preparing Your Environment