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Beginning DAX with Power BI
Philip Seamark
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Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.
Naturwissenschaften, Medizin, Informatik, Technik / Informatik
Beschreibung
Attention all SQL Pros, DAX is not just for writing Excel-based formulas! Get hands-on learning and expert advice on how to use the vast capabilities of the DAX language to solve common data modeling challenges.
Beginning DAX with Power BI teaches key concepts such as mapping techniques from SQL to DAX, filtering, grouping, joining, pivoting, and using temporary tables, all aimed at the SQL professional. Join author Philip Seamark as he guides you on a journey through typical business data transformation scenarios and challenges, and teaches you, step-by-step, how to resolve challenges using DAX. Tips, tricks, and shortcuts are included and explained, along with examples of the SQL equivalent, in order to accelerate learning. Examples in the book range from beginner to advanced, with plenty of detailed explanation when walking through each scenario.
What You’ll Learn
- Turbocharge your Power BI model by adding advanced DAX programming techniques
- Know when to use calculated measures versus calculated columns
- Generate new tables on the fly from existing data
- Optimize, monitor, and tune Power BI to improve performance of your models
- Discover new ideas, tricks, and time-saving techniques for better models
Who This Book Is For
Business intelligence developers, business analysts, or any SQL user who wants to use Power BI as a reporting tool. A solid understanding of SQL is recommended, as examples throughout the book include the DAX equivalents to SQL problem/solution scenarios.
Kundenbewertungen
Data Modelling, Decision Support, Power BI, statistics, Philip Seamark, Spreadsheets, Business Intelligence, SQL, Big Data Programming, Data Insights, DAX