Microsoft power BI cookbook

Microsoft Power BI CookbookCreating Business Intelligence Solutions of Analytical Data Models, Reports, and Dashboards... Automatic data type detection Numeric data types Power BI Deskto

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 retrievalsystem, 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 ofthe information presented However, the information contained in this book is soldwithout 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 thecompanies 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

ISBN 978-1-78829-014-2

www.packtpub.com

Ruben Oliva Ramos

Juan Tomas Oliva Ramos

Acquisition Editor

Varsha Shetty

Indexer

Tejal Daruwale Soni

Content Development Editor

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 thisbook that will first explain the issues and then give a solution on how to achieve thedesired result I, personally, learned something when going through this cookbookand all the recipes provided in it This is a book that can be picked up and referencedwhen looking for solutions for particular challenges or issues Likewise, it is a greatread from cover to cover to expand your skills, which in turn will help build greatPower 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 firstintroduced as the SQL Server 2008R2 PowerPivot add-in for Excel 2010 He hascontributed to the design and development of Microsoft and Power BI solutions ofdiverse scale and complexity across the retail, manufacturing, financial, and servicesindustries Brett regularly blogs and shares technical papers regarding the latest

MSBI and Power BI features and development techniques and patterns at InsightQuest 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 astime 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 BIsince 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 theirbusiness users Gilbert also has an active blog at http://www.fourmoo.com/blog/ This is thefirst 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 inLeon, Guanajuato, Mexico He has more than 5 years of experience in developingweb 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 ofthe master's degree in design and engineering of mechatronics systems Ruben alsoworks at Centro de Bachillerato Tecnologico Industrial 225 in Leon, Guanajuato,Mexico, teaching subjects such as electronics, robotics and control, automation, andmicrocontrollers at Mechatronics Technician Career; he is a consultant and

developer for projects in areas such as monitoring systems and datalogger data usingtechnologies (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 asArduino, 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 Arduinoand 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 hasmore 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 ofprojects since 2011 He became an entrepreneur mentor, and started a new

department of technology management and entrepreneurship at Instituto TecnologicoSuperior 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 forthe 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.

For support files and downloads related to your book, please visit www.PacktPub.com.Did you know that Packt offers eBook versions of every book published, with PDFand ePub files available? You can upgrade to the eBook version at www.PacktPub.com,and as a print book customer, you are entitled to a discount on the eBook copy

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Table of Contents

Preface

What this book covers

What you need for this book

Who this book is for

Piracy Questions

1 Configuring Power BI Development Tools

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

There's more

Guy in a Cube video channel

2 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

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

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

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

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

Active verus inactive customers

Actual versus budget model and measures How it works

Filter Context Functions

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

DAX calculated columns as rare exceptions Natural hierarchies versus unnatural hierarchies Grouping dates and numbers

DirectQuery models supported See also

4 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

Create featured Q&A questions

Parameterized Q&A report

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

How to do it

Dashboard design process

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

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

6 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

Single and multiple URL parameters Dynamic embedded URLs

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

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

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

8 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

FILTERS() and CONCATENATEX() Avoiding manual user clicks with user-based filtering logic

Getting ready How to do it

How it works

There's more

Personal filters feature coming to Power BI apps

9 Applying Advanced Analytics and Custom Visuals

Bullet chart custom visual Scoped quick insights How it works

There's more

Quick insights in Power BI Desktop Quick insights on published datasets Creating geospatial mapping visualizations with ArcGIS maps for Power BI Getting ready

How to do it

Single field address

Customer clustering Map

There's more

ArcGIS map field wells

Conditional formatting logic

Chiclet slicer custom visual

Building animation and story telling capabilities

Getting ready

How to do it

Scatter chart with play axis

ArcGIS map timeline

Pulse chart custom visual

There's more

Bookmarks

Play axis custom visual

Storytelling custom visuals

Embedding statistical analyses into your model

Getting ready

How to do it

Regression table and measures

Residuals table and measures

First purchase date grouping

Days since last purchase grouping Detecting and analyzing clusters

There's more

R clustering custom visuals Scatter chart-based clustering Forecasting and visualizing future results

Getting ready How to do it

Monthly forecast via date hierarchy Weekly sales forecast analysis How it works

Exponential smoothing Dynamic week status column There's more

Forecast requirements Using R functions and scripts to create visuals within Power BI

Getting ready How to do it

Base graphics histogram ggplot2 histogram How it works

Automatic duplicate removal Filter context

Constructing a monitoring visualization and analysis layer

Getting ready How to do it