SQL Query Design Patterns and Best Practices: A practical guide to writing readable and maintainable SQL queries using its design patterns

SQL Query Design Patterns and Best Practices: A practical guide to writing readable and maintainable SQL queries using its design patterns

SQL Query Design Patterns and Best Practices: A practical guide to writing readable and maintainable SQL queries using its design patterns

SQL Query Design Patterns and Best Practices: A practical guide to writing readable and maintainable SQL queries using its design patterns

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Overview

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.


Product Details

ISBN-13: 9781837630080
Publisher: Packt Publishing
Publication date: 03/31/2023
Sold by: Barnes & Noble
Format: eBook
Pages: 270
File size: 18 MB
Note: This product may take a few minutes to download.

About the Author

Steve Hughes is a senior director of data and analytics at 3Cloud. In this role, he focuses on growing the teams’ skills and capabilities to deliver data projects with Azure. In his 20 years of experience in technology, much of the time was spent on creating business intelligence (BI) solutions and helping customers implement BI and cloud solutions. He is passionate about helping customers understand that data is valuable and profitable. Steve has recently been diagnosed with ALS but continues to work and share with others what he has learned. Steve is also the founder of Data on Wheels where he blogs with one of his daughters on topics such as data, analytics, and work enablement
Dennis Neer is a senior architect of data and analytics at 3Cloud. In this role, he focuses on working with clients to design Azure solutions for their data and analytic needs to improve their business decision-making process. This includes using tools such as SQL Server databases, Synapse, data lakes, and Power BI. In his 30 years of experience in technology, much of the time was spent on designing and building database and visualization solutions. He is passionate about helping businesses to understand data and use it to their advantage during their decision-making process
Dr. Ram Babu Singh is a Microsoft Certified Professional with a Ph.D. in computer science. He is a lead architect of data and analytics at 3Cloud, using complex data analytics and data science solutions. In his 20 years of career, over a decade was spent in leadership positions providing data science and data platform solutions to the world’s top IT consulting companies. He has been published in international journals and has a patent in his name
Shabbir H. Mala is a director of data and analytics at 3Cloud. He has over 23 years of experience in thought leadership and consulting, developing complex data solutions, business systems, and processes using Azure Data Services and Power BI. He currently manages a team of over 40 principals and senior architects focusing on business growth, successful project delivery, and client experience. He has done talks at Power BI conferences as well as user groups. He has been awarded Microsoft FastTrack Solution Architect in 2021 and 2022. He is currently living in Chicago, married, and has three beautiful kids
Andrews is a lead data architect of data and analytics at 3Cloud. Working in the IT sector for over 20 years in local government, electrical supply, law enforcement, and healthcare, she has broad experience to draw from to assist clients in making data more accessible for end users. Leslie’s expertise includes SQL development, ETL, data warehousing, data modeling, and analytics. Leslie currently holds several Microsoft certifications related to Azure technologies for data engineering. She approaches each day as an opportunity to use data and technology to make it easier for others to do their daily work. Leslie has been doing public speaking since 2015, was an IDERA ACE in 2019, and is a supporter of and contributor to the SQL community
Chi Zhang is a lead data architect at 3Cloud. After completing her master’s degree at Carnegie Mellon University, she worked in data consulting for the past 5 years. She has helped clients from various industries to deliver customized data solutions within Azure. Focusing on ETL, data warehousing, data modeling, and BI reporting, Chi solves data problems for clients and builds data solutions that provide business users with better operational insights and a smoother experience. Recently, she has continued to grow her footprint in the Azure community: earning certifications in Azure data engineering and data science, giving her first public tech talk, co-authoring a technical book, and becoming an active contributor to the SQL community

Table of Contents

Table of Contents
  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
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