Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Creating Business Intelligence Solutions of Analytical Data Models, Reports, and Dashboards

Brett Powell

BIRMINGHAM - MUMBAI

Microsoft Power BI Cookbook

Copyright © 2017 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: September 2017

Production reference: 1220917

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-78829-014-2

www.packtpub.com

Credits

Foreword

Microsoft Power BI Cookbook is a great example of how to leverage the multitude of features that are available in Power BI. You will find some great examples in this book that will first explain the issues and then give a solution on how to achieve the desired result. I, personally, learned something when going through this cookbook and all the recipes provided in it. This is a book that can be picked up and referenced when looking for solutions for particular challenges or issues. Likewise, it is a great read from cover to cover to expand your skills, which in turn will help build great Power BI Models for your clients/customers.

Gilbert Quevauvilliers,

Microsoft MVP - Power BI & Microsoft Power BI Consultant at Fourmoo

About the Author

Brett Powell is the owner of and business intelligence consultant at Frontline Analytics LLC, a data and analytics research and consulting firm and Microsoft Power BI partner. He has worked with Power BI technologies since they were first introduced as the SQL Server 2008R2 PowerPivot add-in for Excel 2010. He has contributed to the design and development of Microsoft and Power BI solutions of diverse scale and complexity across the retail, manufacturing, financial, and services industries. Brett regularly blogs and shares technical papers regarding the latest MSBI and Power BI features and development techniques and patterns at Insight Quest. He is also an organizer of the Boston BI User Group.

Erin Stellato, featured in Developing Solutions for System Monitoring and Administration, is a principal consultant at SQLskills and Microsoft Data Platform MVP.

I'd first like to thank Varsha Shetty, acquisition editor at Packt, for giving me the opportunity to author this book and her guidance throughout the planning process. I'd also like to thank the Packt board and team for approving the book outline and for their flexibility with page counts and topics. Like most Power BI projects, we followed an agile delivery model in creating this book and this allowed us to include essential details supporting the recipes and the latest Power BI features. Additionally, I'd like to thank Mayur Pawanikar, content editor at Packt, for his thorough reviews and guidance throughout the development process. His contributions were invaluable to the structure and overall quality of the book.

I'd also like to thank Gilbert Quevauvilliers and Juan Tomas Oliva Ramos for their technical reviews and suggestions.

Finally, I'd like to thank the Power BI team for creating such an amazing platform and for everyone around the Power BI community that contributes documentation, white papers, presentations, videos, blogs, and more. 

About the Reviewers

Gilbert Quevauvilliers has been working in the BI space for the past 9 years. He started out learning the basics of business intelligence on the Microsoft stack, and as time went on, he became more experienced. Gilbert has since moved into the Power BI space, after starting out with Power Pivot in Excel 2010. He has used Power BI since its inception and works exclusively in it. He has been recognized with the Microsoft MVP award for his contributions to the community and helping other users.

Gilbert is currently consulting in his own company, called FourMoo (which represents the four family members). Fourmoo provides Microsoft Power BI solutions for business challenges by using customers' data and working with their business users. Gilbert also has an active blog at http://www.fourmoo.com/blog/. This is the first book that he has been asked to review.

I would like to say a big thanks to my wife, Sian, for her endless support and for helping me find the time to review this book.

Ruben Oliva Ramos is a computer systems engineer from Tecnologico de Leon Institute, with a master's degree in computer and electronic systems engineering, teleinformatics, and networking specialization from the University of Salle Bajio in Leon, Guanajuato, Mexico. He has more than 5 years of experience in developing web applications to control and monitor devices connected with Arduino and Raspberry Pi using web frameworks and cloud services to build the Internet of Things applications.

He is a mechatronics teacher at the University of Salle Bajio and teaches students of the master's degree in design and engineering of mechatronics systems. Ruben also works at Centro de Bachillerato Tecnologico Industrial 225 in Leon, Guanajuato, Mexico, teaching subjects such as electronics, robotics and control, automation, and microcontrollers at Mechatronics Technician Career; he is a consultant and developer for projects in areas such as monitoring systems and datalogger data using technologies (such as Android, iOS, Windows Phone, HTML5, PHP, CSS, Ajax, JavaScript, Angular, and ASP.NET), databases (such as SQlite, MongoDB, and MySQL), web servers (such as Node.js and IIS), hardware programming (such as Arduino, Raspberry pi, Ethernet Shield, GPS, and GSM/GPRS, ESP8266), and control and monitor systems for data acquisition and programming.

He wrote Internet of Things Programming with JavaScript by Packt Publishing. He is also involved in the monitoring, controlling, and acquisition of data with Arduino and Visual Basic .NET for Alfaomega.

I would like to thank my savior and lord, Jesus Christ, for giving me the strength and courage to pursue this project; my dearest wife, Mayte; our two lovely sons, Ruben and Dario; my dear father, Ruben; my dearest mom, Rosalia; my brother, Juan Tomas; and my sister, Rosalia, whom I love, for all their support while reviewing this book, for allowing me to pursue my dream, and tolerating not being with them after my busy day job.

Juan Tomás Oliva Ramos is an environmental engineer from the university of Guanajuato, with a master's degree in administrative engineering and quality. He has more than 5 years of experience in management and development of patents, technological innovation projects, and development of technological solutions through the statistical control of processes.

He is a teacher of statistics, entrepreneurship and technological development of projects since 2011. He became an entrepreneur mentor, and started a new department of technology management and entrepreneurship at Instituto Tecnologico Superior de Purisima del Rincon.

He is a Packt Publishing reviewer and he has worked on the book: Wearable designs for Smart watches, Smart TV's and Android mobile devices.

He has developed prototypes through programming and automation technologies for the improvement of operations, which have been registered to apply for his patent. 

I want to thank God for giving me wisdom and humility to review this book.

I want to thank Packt for giving me the opportunity to review this amazing book and to collaborate with a group of committed people.

I want to thank my beautiful wife, Brenda, our two magic princesses, Regina and Renata, and our next member, Angel Tadeo, all of you, give me the strength, happiness and joy to start a new day. Thanks for being my family.

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Table of Contents

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

Configuring Power BI Development Tools

Introduction

Configuring Power BI Desktop options and settings

Getting ready

How to do it...

Installing and running Power BI Desktop

Configuring Power BI Desktop options

How it works...

There's more...

See also

Power BI's advantages over Excel

Power BI Security and Data Source Privacy

Installing the On-Premises Data Gateway

Getting ready

Hardware and network configuration

How to do it...

Installation of on-premises gateway

How it works...

Gateway recovery key

There's more...

See also...

Installing Power BI Publisher for Excel

How to do it...

Installation of Power BI Publisher for Excel

There's more...

Installing and Configuring DAX Studio

How to do it...

Installation of DAX Studio

Configuration of DAX Studio

How it works...

There's more...

Guy in a Cube video channel

Accessing and Retrieving Data

Introduction

Viewing and analyzing M functions

Getting ready

How to do it...

Formula Bar

Advanced Editor window

How it works...

Query folding

M query structure

Lazy evaluation

There's more...

Partial query folding

Limitations of query folding

See also...

M language references

Establishing and managing connections to data sources

Getting ready

How to do it...

Isolate data sources from individual queries

Query groups

Manage source credentials and privacy levels

How it works...

Data Source settings

Data source privacy settings

There's more...

See also

Building source queries for DirectQuery models

Getting ready

How to do it...

Applying M transformations with DirectQuery models

How it works...

There's more...

DirectQuery project candidates

DirectQuery performance

See also

Importing data to Power BI Desktop models

How to do it...

Denormalize a dimension

Provide automatic sorting

How it works...

There's more...

One GB dataset limit and Power BI Premium

See also

Applying multiple filtering conditions

Getting ready

How to do it...

Query filter example steps

How it works...

There's more...

Filtering via the Query Editor interface

See also

Choosing columns and column names

How to do it...

Identify expensive columns

Select columns

Rename columns

How it works...

Column memory usage

There's more...

Fact table column eliminations

Column orders

See also

Transforming and cleansing source data

Getting ready

How to do it...

Remove duplicates

Update a column through a join

There's more...

See also

Creating custom and conditional columns

How to do it...

Create a dynamic banding attribute

Create a formatted name column

Comparing the current and previous rows

How it works...

Conditional expression syntax

Case sensitivity

Conditional expression evaluation

Query folding of custom columns

There's more...

Add column from example

Conditional columns interface

DAX calculated columns

Error handling and comments

Integrating multiple queries

Getting ready

How to do it...

Consolidate files

Self-joining querying

How it works...

Nested join versus flat join

Append multiple files

There's more...

Combine binaries

Staging queries versus inline queries

See also

Choosing column data types

How to do it...

Remove automatic type detection steps

Align relationship column data types

Add numeric columns from text columns

Use fixed decimal number for precision

How it works...

Automatic data type detection

Numeric data types

Power BI Desktop automatic time intelligence

There's more...

Data type impacts

Date with locale

Percentage data type

See also

Visualizing the M library

How to do it...

How it works...

There's more...

Building a Power BI Data Model

Introduction

Designing a multi fact data model

Getting ready

Setting business expectations

How to do it...

Four-step dimensional design process

Data warehouse and implementation bus matrix

Choose the dataset storage mode - Import or DirectQuery

In-Memory mode

DirectQuery mode

How it works...

DAX formula and storage engine

There's more...

Project ingestion questions

Power BI delivery approaches

See also

Implementing a multi fact data model

How to do it...

SQL view layer

M queries in Power BI Desktop

Create model relationships

Author DAX measures

Configure model metadata

There's more...

Shared views

Handling one-to-many and many-to-many relationships

Getting ready

How to do it...

Single, bidirectional, and CROSSFILTER()

Single direction relationships

Bidirectional relationship

CROSSFILTER() Measure

Many-to-many relationships

Bidirectional cross-filtering for many-to-many

How it works...

Ambiguous relationships

CROSSFILTER()

There's more...

DirectQuery supported

See also

Assigning data formatting and categories

How to do it...

Data formats

Data category

How it works...

There's more...

Model level settings

See also

Configuring Default Summarization and sorting

How to do it...

Sort By Column

DAX Year-Month sorting

DAX Ranking Sort

Default Summarization

How it works...

Default Summarization

There's more...

Quick measures

See also

Setting the visibility of columns and tables

How to do it...

Isolate measures from tables

How it works...

Measure home tables

There's more...

Hiding hierarchy columns

Group visibility

Row level security visibility

Visibility features from SSAS

Embedding business definitions into DAX measures

Getting ready

How to do it...

Sales and cost metrics

Margin and count metrics

Secondary relationships

How it works...

Date relationships

There's more...

Measure definitions

Measure names and additional measures

See also

Enriching a model with analysis expressions

How to do it...

Pricing analysis

Geometric mean at all grains

How it works...

Pricing analysis

Building analytics into data models with DAX

How to do it...

Cross-selling opportunities

Accessories but not bike customers

Bike only customers

Active verus inactive customers

Actual versus budget model and measures

How it works...

Filter Context Functions

There's more...

SUMMARIZECOLUMNS()

Integrating math and statistical analysis via DAX

How to do it...

Correlation coefficient

Goodness-of-Fit test statistic

How it works...

Correlation coefficient syntax

Goodness-of-Fit logic and syntax

Supporting virtual table relationships

How to do it...

Segmentation example

Summary to detail example

Actual versus plan

How it works...

Year and month selected

Virtual relationship functions

There's more...

Multiple dimensions 

Alternatives to virtual relationships

See also

Creating browsable model hierarchies and groups

How to do it...

Create hierarchy columns with DAX

Implement a hierarchy

Create and manage a group

How it works...

DAX parent and child functions

Include other grouping option

Model scoped features

There's more...

DAX calculated columns as rare exceptions

Natural hierarchies versus unnatural hierarchies

Grouping dates and numbers

DirectQuery models supported

See also

Authoring Power BI Reports

Introduction

Building rich and intuitive Power BI reports

Getting ready

Stakeholder Matrix

How to do it...

Report planning and design process

Report Design Example

European Sales and Margin Report Page

European country sales and margin report page

How it works...

European sales report design

There's more...

Power BI report design checklist

Custom visuals

Published Power BI datasets as data sources

See also

Creating table and matrix visuals

How to do it...

Table visual exceptions

Identifying blanks in tables

Matrix visual hierarchies

How it works...

Matrix visual navigation

There's more...

URL and mail to email support

Percent of total formatting

Measures on matrix rows

Data bar conditional formatting

Utilizing graphical visualization types

Getting ready

Choosing visual types

How to do it...

Waterfall chart for variance analysis

Line chart with conditional formatting

Shape map visualization

How it works...

Shape map

Enhancing exploration of reports

Getting ready

Drillthrough report page requirements

Enable Cortana integration and Q&A

How to do it...

Create featured Q&A questions

Parameterized Q&A report

Cortana integration

Drillthrough Report Pages

Report themes

How it works...

Report theme JSON files

There's more...

Conversational BI - mobile support for Q&A

See also

Integrating card visualizations

Getting ready

How to do it...

KPI visual

Multi-row card

There's more...

Gauge visualizations

Controlling interactive filtering between visuals

How to do it...

Visual interaction control

How it works...

Current year Measures

Associating slicers with report pages

How to do it...

Configure dimension slicers

Horizontal slicers

Customize a date slicer

Relative date filters

How it works...

Date slicer

There's more...

Text search

Numeric range slicers

Applying filters at different scopes

How to do it...

Report and page level filters

Visual level filter - top N

How it works...

DAX queries from report, page, and visual Filters

There's more...

Advanced report and page level filters

Formatting reports for publication

How to do it...

Visual alignment and distribution

Shapes as backgrounds and groups

There's more...

Snap objects to grid and keyboard shortcuts

Textbox with email link

Format painter

See also

Designing mobile report layouts

Getting ready

Plan for mobile consumption

How to do it...

Phone layout - Europe report page

Phone layout - United Kingdom report page

How it works...

There's more...

Slicers and drill-down on mobile devices

Mobile-optimized dashboards

See also

Creating Power BI Dashboards

Introduction

Building a Power BI dashboard

How to do it...

Dashboard design process

Dashboard development process

Constructing an enterprise dashboard

How to do it...

Dashboard design process

How it works...

Dual KPI custom visual

Supporting tiles

Developing dynamic dashboard metrics

How to do it...

Dynamic date columns

KPI target measures

How it works...

Target measure - trailing 6 months

Preparing datasets and reports for Q & A natural language queries

Getting ready

Determine use cases and feasibility

How to do it...

Prepare a model for Q & A

Model metadata

Model design

Apply synonyms

Analyze Q & a use cases

Apply synonyms

Publish the dataset

Embedding analytical context into visualizations

How to do it...

Design the visual

Create the visual

How it works...

Color saturation rule

Tooltip measures

There's more...

Exposing what matters - top N and percentage of total visualizations

How to do it...

Top 25 resellers with below -3% margin

Last year's top 50 products with below -10% growth

How it works...

Prior year rank measure

Visualizing performance relative to targets with KPIs and gauges

How to do it...

Create the visuals

Grouping KPIs

Publish KPIs to dashboard

How it works...

Current month filter

Time intelligence measures

Leveraging Power BI reports in Power BI dashboards

How to do it...

Define live page requirements

Create and publish to the dashboard

Refine dashboard layout

How it works...

Live page slicers

Deploying content from Excel and SSRS to Power BI

Getting ready

How to do it...

Publish and pin excel objects

Pin SSRS report items

Adding data alerts and email notifications to dashboards

How to do it...

Configure data alert

Automate email notification

How it works...

Getting Serious with Date Intelligence

Introduction

Building a complete date dimension table

Getting ready

How to do it...

Date dimension design

Required date dimension columns

Date dimension planning and design

Add date intelligence columns via SQL

How it works...

Date intelligence columns

Loading the date dimension

There's more...

Role playing date dimensions

Surrogate key date conversion

Prepping the date dimension via the Query Editor

How to do it...

Date dimension M Query

Add the date intelligence column via join

How it works...

Date dimension M query

DirectQuery support

Authoring date intelligence metrics across granularities

Getting ready

How to do it...

Current time period measures

Prior time period measures

Dynamic prior period measure

How it works...

Current and prior time period measures

Developing advanced date intelligence metrics

How to do it...

Count of days without sales

Dynamic Prior Year-to-Date

How it works...

Dynamic prior period intelligence

Simplifying date intelligence with DAX queries and calculated tables

How to do it...

Role playing date dimensions via calculated tables

Date table logic query

How it works...

Date table logic query

Adding a metric placeholder dimension

How to do it...

Metric placeholder dimension query

Measure group table

Parameterizing Power BI Solutions

Introduction

Creating dynamic and portable Power BI reports

Getting ready

How to do it...

Single and multiple URL parameters

Dynamic embedded URLs

There's more...

Dashboards with custom URLs

See also

Filtering queries with parameters

Getting ready

How to do it...

Trailing days query parameter filter

Multi-parameter query filters

How it works...

Query folding of parameter value filters

There's more...

Power BI Service support

Preserving report metadata with Power BI templates

Getting ready

How to do it...

Template parameters

Export template

Converting static queries into dynamic functions

How to do it...

There's more...

Local resource usage

Parameterizing your data sources

Getting ready

How to do it...

SQL Server database

Excel filename and path

Stored procedure input parameters

Generating a list of parameter values via queries

How to do it...

Dynamic date parameter query

Product subcategories parameter query

There's more...

DirectQuery support

Capturing user selections with parameter tables

How to do it...

Sales plan growth scenarios

There's more...

Scenario specific measures

Building a forecasting process with What if analysis capabilities

Getting ready

How to do it...

Forecast variables from Excel

Power BI Desktop forecast model

Source connection and unpivoted forecast tables

Apply the forecast to historical values

Allocate the forecast according to the dimension variable inputs

Create relationships, measures, and forecast visuals

Test and deploy forecasting tool

How it works...

Implementing Dynamic User-Based Visibility in Power BI

Introduction

Capturing the current user context of Power BI content

Getting ready

How to do it...

How it works...

Power BI authentication

There's more...

USERNAME() versus USERPRINCIPALNAME()

See also

Defining RLS roles and filtering expressions

Getting ready

How to do it...

United States online Bike Sales Role

Europe reseller sales - mountain and touring

Deploy security roles to Power BI

How it works...

Filter transfer via relationships

There's more...

Managing security

Dynamic columns and central permissions table

Designing dynamic security models in Power BI

Getting ready

How to do it...

There's more...

Performance impact

Building dynamic security in DirectQuery data models

Getting ready

How to do it...