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Optimizing DAX
Optimizing DAX
Knygos.lt klubas Knygos.lt nariams
92,95 €
-30%
Įprastai
132,79 €
  • Išsiųsime per 12–18 d.d.
This book is the state of the art of optimizing DAX expressions in Power BI and Analysis Services semantic models. Learn how to locate performance bottlenecks, read the query plan and performance metrics, rewrite the slower part of an expression, and measure the performance improvements.Use tools like Power BI Desktop Performance Analyzer and DAX StudioUnderstand the DAX formula engine Learn characteristics of different storage engines (VertiPaq, DirectQuery over SQL)Read DAX query plansOptimiz…
  • Leidėjas:
  • ISBN-10: 173536522X
  • ISBN-13: 9781735365220
  • Formatas: 19.1 x 23.5 x 4.1 cm, minkšti viršeliai
  • Kalba: Anglų

Optimizing DAX (el. knyga) (skaityta knyga) | Alberto Ferrari | knygos.lt

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This book is the state of the art of optimizing DAX expressions in Power BI and Analysis Services semantic models. Learn how to locate performance bottlenecks, read the query plan and performance metrics, rewrite the slower part of an expression, and measure the performance improvements.

  • Use tools like Power BI Desktop Performance Analyzer and DAX Studio
  • Understand the DAX formula engine
  • Learn characteristics of different storage engines (VertiPaq, DirectQuery over SQL)
  • Read DAX query plans
  • Optimize common DAX constructs
  • Solve security performance issues
  • Improve DirectQuery response time
  • Control the data placement in composite models to avoid bottlenecks

Prerequisites: proficiency in DAX and SQL (for DirectQuery), understanding of the Tabular engine used by semantic models, and familiarity with DAX Studio.

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  • Autorius: Alberto Ferrari
  • Leidėjas:
  • ISBN-10: 173536522X
  • ISBN-13: 9781735365220
  • Formatas: 19.1 x 23.5 x 4.1 cm, minkšti viršeliai
  • Kalba: Anglų

This book is the state of the art of optimizing DAX expressions in Power BI and Analysis Services semantic models. Learn how to locate performance bottlenecks, read the query plan and performance metrics, rewrite the slower part of an expression, and measure the performance improvements.

  • Use tools like Power BI Desktop Performance Analyzer and DAX Studio
  • Understand the DAX formula engine
  • Learn characteristics of different storage engines (VertiPaq, DirectQuery over SQL)
  • Read DAX query plans
  • Optimize common DAX constructs
  • Solve security performance issues
  • Improve DirectQuery response time
  • Control the data placement in composite models to avoid bottlenecks

Prerequisites: proficiency in DAX and SQL (for DirectQuery), understanding of the Tabular engine used by semantic models, and familiarity with DAX Studio.

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