Autorentext

Markus Ehrenmueller-Jensen is the founder of Savory Data and has worked as a project leader, trainer & consultant for data engineering, business intelligence, and data science since 1994. He is an educated software engineer, graduated business educator, and professor for databases and project engineering at HTL Leonding (technical college) and certified in MCSE Data Platform, MCSE Business Intelligence, and MCT. Markus speaks regularly at international conferences (eg. PASS Summit, SQLBits, SQL Saturdays, SQL Days, Power BI World Tour, ...) and writes articles for well-known journals. He is the author of "Self-Service AI in Power BI Desktop" (Apress, 2020) and co-author of "Power BI MVP Book" (Amazon, 2019). In 2013 he co-founded Data Community Austria (formerly known as SQL PASS Austria and Power BI Usergroup Austria) and has organized Data Saturdays in Austria since 2014. For his technical leadership in the community, he was awarded as a Microsoft Data Platform MVP in 2017.

Klappentext

Data modeling is the single most overlooked feature in Power BI Desktop, yet it's what sets Power BI apart from other tools on the market. This practical book serves as your fast-forward button for data modeling with Power BI, Analysis Services tabular, and SQL databases. It serves as a starting point for data modeling, as well as a handy refresher. Author Markus Ehrenmueller-Jensen, founder of Savory Data, shows you the basic concepts of Power BI's semantic model with hands-on examples in DAX, Power Query, and T-SQL. If you're looking to build a data warehouse layer, chapters with T-SQL examples will get you started. You'll begin with simple steps and gradually solve more complex problems. This book shows you how to:

• Normalize and denormalize with DAX, Power Query, and T-SQL
• Apply best practices for calculations, flags and indicators, time and date, role-playing dimensions and slowly changing dimensions
• Solve challenges such as binning, budget, localized models, composite models, and key value with DAX, Power Query, and T-SQL
• Discover and tackle performance issues by applying solutions in DAX, Power Query, and T-SQL
• Work with tables, relations, set operations, normal forms, dimensional modeling, and ETL