The Definitive Guide to DAX(2019年Microsoft Press出版的圖書)

The Definitive Guide to DAX(2019年Microsoft Press出版的圖書)

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《The Definitive Guide to DAX》是Microsoft Press出版的圖書,作者是Marco Russo,Alberto Ferrari

基本介紹

  • ISBN:9781509306978
  • 作者:Marco Russo、Alberto Ferrari
  • 出版社:Microsoft Press
  • 出版時間:2019年7月20日
  • 頁數:768
  • 定價:USD 54.99
  • 裝幀:Paperback
內容簡介
Now expanded and updated with modern best practices, this is the most complete guide to Microsoft’s DAX language for business intelligence, data modeling, and analytics. Expert Microsoft BI consultants Marco Russo and Alberto Ferrari help you master everything from table functions through advanced code and model optimization. You’ll learn exactly what happens under the hood whe...(展開全部) Now expanded and updated with modern best practices, this is the most complete guide to Microsoft’s DAX language for business intelligence, data modeling, and analytics. Expert Microsoft BI consultants Marco Russo and Alberto Ferrari help you master everything from table functions through advanced code and model optimization. You’ll learn exactly what happens under the hood when you run a DAX expression, and use this knowledge to write fast, robust code. This edition focuses on examples you can build and run with the free Power BI Desktop, and helps you make the most of the powerful syntax of variables (VAR) in Power BI, Excel, or Analysis Services. Want to leverage all of DAX’s remarkable capabilities? This no-compromise “deep dive” is exactly what you need. Perform powerful data analysis with DAX for Power BI, SQL Server, and Excel · Master core DAX concepts, including calculated columns, measures, and calculation groups · Work efficiently with basic and advanced table functions · Understand evaluation contexts and the CALCULATE and CALCULATETABLE functions · Perform time-based calculations · Use calculation groups and calculation items · Use syntax of variables (VAR) to write more readable, maintainable code · Express diverse and unusual relationships with DAX, including many-to-many relationships and bidirectional filters · Master advanced optimization techniques, and improve performance in aggregations · Optimize data models to achieve better compression ·

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