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  • Book Overview & Buying Extreme DAX
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Extreme DAX

Extreme DAX

By : Michiel Rozema, Henk Vlootman
4.9 (45)
Buy this Book
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Extreme DAX

Extreme DAX

4.9 (45)
By: Michiel Rozema, Henk Vlootman
Buy this Book

Overview of this book

This book helps business analysts generate powerful and sophisticated analyses from their data using DAX and get the most out of Microsoft Business Intelligence tools. Extreme DAX will first teach you the principles of business intelligence, good model design, and how DAX fits into it all. Then, you’ll launch into detailed examples of DAX in real-world business scenarios such as inventory calculations, forecasting, intercompany business, and data security. At each step, senior DAX experts will walk you through the subtleties involved in working with Power BI models and common mistakes to look out for as you build advanced data aggregations. You’ll deepen your understanding of DAX functions, filters, and measures, and how and when they can be used to derive effective insights. You’ll also be provided with PBIX files for each chapter, so that you can follow along and explore in your own time.
Table of Contents (17 chapters)
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Preface
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Preface
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Who this book is for
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What this book covers
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To get the most out of this book
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Get in touch
Lock Free Chapter
1
Part I: Introduction
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Part I: Introduction
2
1.1 DAX in Business Intelligence
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1.1 DAX in Business Intelligence
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The Five-Layer model for business intelligence
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Enterprise BI and end-user BI
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Where DAX fits in, and where to find it
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Tools to develop models and DAX
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Powered by DAX: visual, interactive reports
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How to approach solution development
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The digital transformation cycle
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Summary
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1.2 Model Design
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1.2 Model Design
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Columnar data storage
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Data types and encoding
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Relationships
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Effective model design
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Memory and performance considerations
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Summary
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1.3 Using DAX
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1.3 Using DAX
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Calculated columns
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Calculated tables
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Measures
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DAX security filters
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DAX queries
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Date tables
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Best practices in DAX
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Summary
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1.4 Context and Filtering
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1.4 Context and Filtering
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The Power BI model
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Introduction to DAX context
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DAX filtering: Using CALCULATE
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Time intelligence
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Changing relationship behavior
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Table functions in DAX
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Filtering with table functions
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DAX variables
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Summary
6
Part II: Business cases
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Part II: Business cases
7
2.1 Security with DAX
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2.1 Security with DAX
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Introduction to row-level security (RLS)
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Securing hierarchies using PATH functions
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Securing attributes
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Securing aggregation levels
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Summary
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2.2 Dynamically Changing Visualizations
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2.2 Dynamically Changing Visualizations
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The business case
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Dynamic measures
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Dynamic labels
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Combining dynamic labels and dynamic calculations
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Summary
9
2.3 Alternative Calendars
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2.3 Alternative Calendars
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Week-based and Gregorian calendars
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Creating a week-based calendar table
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Time Intelligence calculations for week-based calendars
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Keeping your report current
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Summary
10
2.4 Working with AutoExist
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2.4 Working with AutoExist
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The Power BI model
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How Power BI visualizes the output of a model
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What AutoExist is, and what it does
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Example: The case of the missing workdays
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How to solve the missing workdays problem
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Optimizing report performance with AutoExist
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Summary
11
2.5 Intercompany Business
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2.5 Intercompany Business
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Modeling the QuantoBikes sales process
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Business between subsidiaries
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Future sales
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Summary
12
2.6 Exploring the Future: Forecasting and Future Values
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2.6 Exploring the Future: Forecasting and Future Values
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Financial calculations
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Financial DAX functions
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The business case and model
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Calculating Future Value (FV)
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Calculating Net Present Value (NPV)
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Calculating the Internal Rate of Return (IRR)
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Calculating cost-covering rent
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Summary
13
2.7 Inventory Analysis
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2.7 Inventory Analysis
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Data modeling for status-oriented data
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Basic inventory calculations
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Inventory forecasting
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Summary
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2.8 Personnel Planning
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2.8 Personnel Planning
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The Power BI model
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Calculating sales
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Calculating FTEs needed
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Optimizing the Power BI model
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Considering aggregation levels
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Summary
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Other Books You May Enjoy
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Other Books You May Enjoy
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Index
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Index

Columnar data storage

The power of the Power BI model comes primarily from a smart data storage mechanism. Power BI models are, in fact, databases in the sense that they organize and store data. But the internals are very different from other database technologies you may be familiar with.

Relational databases

The traditional, corporate way of working with data is with a relational database management system (RDBMS) like Microsoft SQL Server. In an RDBMS, tables of data are defined with a fixed number of data columns per table. Each column must have a data type, like integer, text, or decimal number, and from this information, the RDBMS can derive how much space is needed to store a single row of data, or record, and how many rows can be stored in a disk-based data file. This concept makes an RDBMS an effective choice for applications that process transactions, like sales transactions from a web shop or transactions in a company's financial ledger.

The concept of...

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Tech Concepts
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Programming languages
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