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SQL Query Design Patterns and Best Practices A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns /

Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine query design and performance using query plans and indexe...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Hughes, Steve (Autor), Neer, Dennis (Autor), Singh, Ram Babu (Autor), Mala, Shabbir H. (Autor), Andrews, Leslie (Autor), Zhang, Chi (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited, 2023.
Edición:1st edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |a SQL Query Design Patterns and Best Practices  |h [electronic resource] :  |b A Practical Guide to Writing Readable and Maintainable SQL Queries Using Its Design Patterns /  |c Steve Hughes, Dennis Neer, Dr. Ram Babu Singh, Shabbir H. Mala, Leslie Andrews, Chi Zhang. 
250 |a 1st edition. 
260 |a Birmingham :  |b Packt Publishing, Limited,  |c 2023. 
300 |a 1 online resource (270 p.) 
500 |a Description based upon print version of record. 
505 0 |a Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Refining Your Queries to Get the Results You Need -- Chapter 1 -- Reducing Rows and Columns in Your Result Sets -- Technical requirements -- Identifying data to remove from the dataset -- Reducing the amount of data -- Understanding the value of creating views versus removing data -- Exploring the impact of row and column reductions on aggregations -- Summary -- Chapter 2 -- Efficiently Aggregating Data -- Technical requirements -- Identifying data to be aggregated 
505 8 |a Determining when data should be aggregated -- The AVG() function -- The SUM() function -- The COUNT() function -- The MAX() function -- The MIN() Function -- Improving performance when aggregating data -- Summary -- Chapter 3 -- Formatting Your Results for Easier Consumption -- Technical requirements -- Using the FORMAT() function -- Format() with culture -- Format() with custom formatting strings -- Formatting dates and numbers with functions -- Formatting dates and numbers with CONVERT() and CAST() -- Formatting numbers with ROUND() and CEILING() -- Comparing FORMAT(), CONVERT(), and CAST() 
505 8 |a Alias columns with meaningful names -- Summary -- Chapter 4 -- Manipulating Data Results Using Conditional SQL -- Technical requirements -- Using the CASE statement -- Using a simple CASE expression in a SELECT statement -- Using a searched CASE expression in a SELECT statement -- Using CASE in an ORDER BY statement -- Using CASE in an UPDATE statement -- Using CASE in a HAVING statement -- Using the COALESCE() expression -- How to use COALESCE() -- Comparing COALESCE() and CASE() -- Using ISNULL() function -- How to use ISNULL() -- Comparing ISNULL() and COALESCE() -- Summary 
505 8 |a Part 2: Solving Complex Business and Data Problems in Your Queries -- Chapter 5 -- Using Common Table Expressions -- Technical requirements -- Creating CTEs -- Set theory for queries -- Creating a more complex CTE -- Creating a recursive CTE -- Creating the hierarchical data -- Creating the recursive CTE -- Recursive alternative -- Summary -- Chapter 6 -- Analyze Your Data Using Window Functions -- Technical requirements -- Understanding window functions -- Using a window function in a query -- Adding a partition to the results -- Window functions with frames -- Scenarios and business problems 
505 8 |a Days between orders -- Finding a pattern -- Finding first N records of every group -- Running totals -- First and last record in the partition -- Year-over-year growth -- Chapter 7 -- Reshaping Data with Advanced Techniques -- Technical requirements -- Working with the PIVOT operator -- Using PIVOT dynamically -- Working with the UNPIVOT operator -- Understanding hierarchical data -- Summary -- Chapter 8 -- Impact of SQL Server Security on Query Results -- Technical requirements -- Why is data missing from my result set? -- Understanding SQL Server security -- Validating security settings 
500 |a Summary 
520 |a Enhance your SQL query writing skills to provide greater business value using advanced techniques such as common table expressions, window functions, and JSON Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine query design and performance using query plans and indexes Solve business problems using advanced techniques such as common table expressions and window functions Use SQL in modern data platform solutions with JSON and Jupyter notebooks Book Description 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. What you will learn Build efficient queries by reducing the data being returned Manipulate your data and format it for easier consumption Form common table expressions and window functions to solve complex business issues Understand the impact of SQL security on your results Understand and use query plans to optimize your queries Understand the impact of indexes on your query performance and design Work with data lake data and JSON in SQL queries Organize your queries using Jupyter notebooks Who this book is for This book is for SQL developers, data analysts, report writers, data scientists, and other data gatherers looking to expand their skills for complex querying as well as for building more efficient and performant queries. For those new to SQL, this book can help you accelerate your learning and keep you from making common mistakes. 
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700 1 |a Neer, Dennis,  |e author. 
700 1 |a Singh, Ram Babu,  |e author. 
700 1 |a Mala, Shabbir H.,  |e author. 
700 1 |a Andrews, Leslie,  |e author. 
700 1 |a Zhang, Chi,  |e author. 
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