Analyzing Data with Power BI and Power Pivot for Excel

✍ Scribed by Ferrari, Alberto;Russo, Marco

• Publisher: Pearson Education
• Year: 2017
• Tongue: English
• Leaves: 250
• Series: Business Skills
• Category: Library

✦ Synopsis

Get started quickly with Microsoft Power BI! Experts Alberto Ferrari and Marco Russo will help you bring your data to life, transforming your company's data into rich visuals for you to collect and organize, allowing you to focus on what matters most to you. Stay in the know, spot trends as they happen, and push your business to new limits. This free ebook introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Read the ebook to get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples. Introducing Microsoft Power BI enables you to evaluate when and how to use Power BI. Get inspired to improve business processes in your company by leveraging the available analytical and collaborative features of this environment. Be sure to watch for the publication of Alberto Ferrari and Marco Russo's upcoming retail book, Analyzing Data with Power BI and Power Pivot for Excel (ISBN 9781509302765). Go to the book's page at the Microsoft Press Store here for more details:http://aka.ms/analyzingdata/details. Learn more about Power BI at https://powerbi.microsoft.com/.

✦ Table of Contents

Cover
Title Page
Copyright Page
Contents
Introduction
Chapter 1 Introduction to data modeling
Working with a single table
Introducing the data model
Introducing star schemas
Understanding the importance of naming objects
Conclusions
Chapter 2 Using header/detail tables
Introducing header/detail
Aggregating values from the header
Flattening header/detail
Conclusions
Chapter 3 Using multiple fact tables
Using denormalized fact tables
Filtering across dimensions
Understanding model ambiguity
Using orders and invoices
Calculating the total invoiced for the customer
Calculating the number of invoices that include the given order of the given customer
Calculating the amount of the order, if invoiced
Conclusions
Chapter 4 Working with date and time
Creating a date dimension
Understanding automatic time dimensions
Automatic time grouping in Excel
Automatic time grouping in Power BI Desktop
Using multiple date dimensions
Handling date and time
Time-intelligence calculations
Handling fiscal calendars
Computing with working days
Working days in a single country or region
Working with multiple countries or regions
Handling special periods of the year
Using non-overlapping periods
Periods relative to today
Using overlapping periods
Working with weekly calendars
Conclusions
Chapter 5 Tracking historical attributes
Introducing slowly changing dimensions
Using slowly changing dimensions
Loading slowly changing dimensions
Fixing granularity in the dimension
Fixing granularity in the fact table
Rapidly changing dimensions
Choosing the right modeling technique
Conclusions
Chapter 6 Using snapshots
Using data that you cannot aggregate over time
Aggregating snapshots
Understanding derived snapshots
Understanding the transition matrix
Conclusions
Chapter 7 Analyzing date and time intervals
Introduction to temporal data
Aggregating with simple intervals
Intervals crossing dates
Modeling working shifts and time shifting
Analyzing active events
Mixing different durations
Conclusions
Chapter 8 Many-to-many relationships
Introducing many-to-many relationships
Understanding the bidirectional pattern
Understanding non-additivity
Cascading many-to-many
Temporal many-to-many
Reallocating factors and percentages
Materializing many-to-many
Using the fact tables as a bridge
Performance considerations
Conclusions
Chapter 9 Working with different granularity
Introduction to granularity
Relationships at different granularity
Analyzing budget data
Using DAX code to move filters
Filtering through relationships
Hiding values at the wrong granularity
Allocating values at a higher granularity
Conclusions
Chapter 10 Segmentation data models
Computing multiple-column relationships
Computing static segmentation
Using dynamic segmentation
Understanding the power of calculated columns: ABC analysis
Conclusions
Chapter 11 Working with multiple currencies
Understanding different scenarios
Multiple source currencies, single reporting currency
Single source currency, multiple reporting currencies
Multiple source currencies, multiple reporting currencies
Conclusions
Appendix A: Data modeling 101
Tables
Data types
Relationships
Filtering and cross-filtering
Different types of models
Star schema
Snowflake schema
Models with bridge tables
Measures and additivity
Additive measures
Non-additive measures
Semi-additive measures
Index
A
B
C
D
E
F
G
H
I
K-L
M
N
O
P
R
S
T
U
V
W
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