Optimizing DAX : Improving DAX performance in Microsoft Power BI and Analysis Services

Alberto Ferrari

ISBN 10: 173536522X / ISBN 13: 9781735365220

Published by SQLBI Corp., 2024

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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 engineLearn characteristics of different storage engines (VertiPaq, DirectQuery over SQL)Read DAX query plansOptimize common DAX constructsSolve security performance issuesImprove DirectQuery response timeControl the data placement in composite models to avoid bottlenecksPrerequisites: proficiency in DAX and SQL (for DirectQuery), understanding of the Tabular engine used by semantic models, and familiarity with DAX Studio.

Seller Inventory # 9781735365220

Bibliographic Details

• Title: Optimizing DAX : Improving DAX performance in Microsoft Power BI and Analysis Services
• Publisher: SQLBI Corp.
• Publication Date: 2024
• Language: English
• ISBN 10: 173536522X
• ISBN 13: 9781735365220
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 235W x 191H x 44D millimeters 235 millimeters width by 191 millimeters height by 44 millimeters depth
• Weight: 1496 grams

About this title

Synopsis

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.