PowerBI_Tutorial

PowerBI Tutorial (Jack Hyman)

Get the book –

• Amazon: https://www.amazon.com/Microsoft-Power-Dummies-Jack-Hyman/dp/1119824877
• Wiley: https://www.wiley.com/en-us/Microsoft+Power+BI+For+Dummies-p-9781119824893

Part 0: Introduction

0.0 Preface

What does Business Intelligence (BI) require?

Basic: querying data sources, reporting, caching data, and visualizing data

If you had to address your organization’s needs, what would they do?

Would taking structured, unstructured, and semistructured data and making sense of it be part of your organizational requirements?

Perhaps developing robust business analytics outputs for executive consumption?

Is the mandate from the leadership the delivery of complex reports, visualizations, dashboards, and key performance indicators?

Brief history of Power BI

Power BI was initially conceived as part of the SQL Server Reporting Team back in 2010.

Then, Power BI made its way into the Office 365 suite in September 2013 as an advanced analytics product.

Power BI was built around Microsoft Excel core add-ins: Power Query, Power Pivot, and Power View.

Along the way, Microsoft added a few artificial intelligence features, such as the Q&A Engine, enterprise-level data connectors, and security options via the Power BI Gateway.

The product became so popular with the enterprise business community that, in July of 2015, Power BI was separated from the Office family, becoming its own product line.

Finally, in late 2019, Power BI merged with other Microsoft products to form the Power Platform family, which consists of Power Apps (mobile), Power Automate (workflow), and Power BI (business intelligence)

0.1 About this Book

Target Audience

Anyone interested in business analytics, focusing as it does on the general platform capabilities across the Power BI platform

What will be learnt from here?

Business Analysts who need to find a tool as the source to complete variable critical tasks in your field

Data Professionals who wish to understand the foundational activities across the Power BI platform into using Microsoft’s business intellegence (BI) platform

Developers who want to find tips, tricks and techniques from Power BI (or beyond) especially DAX area

IT Professionals that can treat this as a starting point if you want to enter the world of Microsoft enterprise business intelligence

Managers or Executives to get understand of the Power BI product which help your to bring guidelines for business intelligence requirements to the team

0.2 Foolish Assumptions

This book/course is for users who want to learn about the critical features across the 3 Power BI platforms: Desktop, Services and Mobile

Have already downloaded a copy of Power BI Desktop

Have at least signed up for a Power BI Free Services account, but preferably have a Power BI Pro account

Have access to the Internet

Have a meaningful dataset

0.3 Icons Used in This Book: Tip, Remember, Technical Stuff, On the Way, Warning

0.4 Beyond the Book

Power BI for Dummies Cheat Sheet

Another cheat sheet: https://www.dummies.com/article/technology/information-technology/data-science/general-data-science/microsoft-power-bi-for-dummies-cheat-sheet-289744/

Sample Dataset

Part 1: Put Your BI Thinking Caps On

Learning Outcomes:

• Get introduced to the types of data used in enterprise BI solutions
• Identify the roles, responsibilities, and products produced by BI professionals
• Discover the licensing options and core features available with Power BI

CH01 A Crash Course in Data Analytics Terms: Power BI Styles

Chapter Learning Outcomes:

• Figuring out the different types of data Power BI can handle
• Understanding your options for business intelligence tooling
• Familiarizing yourself with Power BI terminology

01.0 Preface

Dealing with data isn’t always a chore (苦差事) – data be be fund to explore as well

01.1 What is Data, Really?

Data contains facts. Sometimes, the facts make sense; sometimes, they’re meaningless unless you add a bit of context.

Information is the collective body of all the data parts, that results in the factoids making logical sense

01.1.1 Working with Structured Data

(see:)

Structured data conforms to a tabular format, meaning that each column and row must maintain an interrelationship.

In Power BI, the structured data conform to a formal specification of tables with rows and columns, commonly referred to as adata schema.

The most accessible data sources for BI tools are structured

Platforms that offer robust structured data options:

Microsoft SQL Server

Microsoft Azure SQL Server

Microsoft Access

Azure Table Storage

Oracle

IBM DB2

MySQL

PostgreSQL

Microsoft Excel

Google Sheets

01.1.2 Looking at Unstructured Data

(see:)

Video, audio, photo, or text file is considered unstructured data

01.1.3 Adding Semistructured Data to the Mix

(see:)

Semistructured data contains tags that make the data easier to organize in some form of hierarchy.

Nonrelational data system or NoSQL databases are best associated with semistructured data.

If the serialized language can communicate and speak the same language, a semistructured dataset has great potential

01.2 Looking Under the Power BI Hood (引擎罩, 兜帽)

Power BI is a product that brings together many smaller, cloud-based apps and services with a specific objective: to organize, collect, manage, and analyze big datasets.

Power Query: a data connection tool you can use to transform, combine, and enhance data across several data sources

Power Pivot: a data modeling tool

Power View: a data visualization tool you can use to generate interactive charts, graphs, maps and visuals

Power Map: a visualization tool for creating 3D map renderings

Power Q&A: an artificial intelligence engine that allows you to ask questions and receive responses using plain language

Power BI Desktop: a free, all-in-one solution that brings together all the apps described in this list into a single graphical user interface

Power BI Services: a cloud-based user experience to collaborate and distribute products such as reports with others

Big Data is a concept where the buisness and data analyst will evaluate extremely large datasets, which may reveal patterns and trends relating to human behaviors and interactions not easily identifiable without the use of specific tools.

01.2.1 Posing Questions with Power Query

Before Power BI became its own product line, it was originally an advanced query and data manipulation add-in for Excel, circa (大约) 2010

One of the justifications for the switch to a dedicated product was the need for a more robust query editor.

With the Excel editor, it was a single data source

With Power BI’s Power Query, you can extract data from numerous data sources

01.3 Knowing Your Power BI Terminology

01.4 Business Intelligent (BI): The Definition

CH02 The Who, How, and What of Power BI

02.1 Highlighting the Who of Power BI

02.2 Understanding How Data Comes to Life

02.3 Examining the Various Types of Data Analytics

02.4 Taking a Look at the Big Picture

CH03 Oh, the Choices: Power BI Versions

03.1 Why Power BI versus Excel?

03.2 Power BI Products in a Nutshell

03.3 Examining the Details of the Licensing Options

03.4 On the Road with Power BI Mobile

03.5 Working with Power BI Report Server

03.6 Linking Power BI and Azure

CH04 Power BI: The Highlights

04.1 Power BI Desktop: A Top-Down View

04.2 Services: Far and Wide

Part 2: It’s Time to Have a Data Party

CH05 Preparing Data Sources

05.1 Getting Data from the Source

05.2 Managing Data Source Settings

05.3 Working with Shared versus Local Datasets

05.4 Storage Modes

05.5 Considering the Query

05.6 Exporting Power BI Desktop Files and Leveraging XMLA

CH06 Getting Data from Dynamic Sources

06.1 Getting Data from Microsoft-Based File Systems

06.2 Working with Relational Data Sources

06.3 Importing Data from a Non-relational Data Source

06.4 Importing JSON File Data into Power BI

06.5 Importing Data from Online Sources

06.6 Creating Data Source Combos

06.7 Dealing with Modes for Dynamic Data

06.8 Fixing Data Import Errors

CH07 Cleaning, Transforming, and Loading Your Data

07.1 Engaging Your Detective Skills to Hunt Down Automalies and Inconsistencies

07.2 Stepping through the Data Lifecycle

07.3 Evaluating the Transforming Column Data Types

07.4 Tweaking Power Query’s M Code

07.5 Configuring Queries for Data Loading

07.6 Resolving Errors During Data Import

Part 3: The Art and Science of Power BI

CH08 Crafting the Data Model

08.1 An Introduction to Data Models

08.2 Dealing with Table and Column Properties

08.3 Managing Cardinality and Direction

08.4 Data Granularity

CH09 Designing and Deploying Data Models

09.1 Creating a Data Model Masterpiece

09.2 Managing Relationships

09.3 Arranging Data

09.4 Working with Extended Data Models

09.5 Publishing Data Models

CH10 Perfecting the Data Model

10.1 Matching Queries with Capacity

CH11 Visualizing Data

11.1 Looking at Report Fundamentals and Visualizations

11.2 Dealing with Table-Based and Complex Visualizations

11.3 Dabbling in Data Science

11.4 Questions and Answers

CH12 Pumping Out Reports

12.1 Formatting and Configuring Report Visualizations

12.2 Filtering and Sorting

12.3 Configuring the Report Page

12.4 Refreshing Data

CH13 Diving into Dashboarding

13.1 Configuring Dashboards

13.2 Creating a New Dashboard

13.3 Enriching Your Dashboard with Content

13.4 Pinning Reports

13.5 Customizing with Themes

13.6 Working with Dashboard Layouts

13.7 Integrating Q&A

13.8 Setting Alerts

Part 4: Oh, No! There’s a Power BI Programming Language!

CH14 Digging Into DAX

14.1 Discovering DAX

14.2 Dealing with Data Types

14.3 Operating with Operators

14.4 Making a Statement

14.5 Ensuring Compatibility

CH15 Fun with DAX Functions

15.1 Working with DAX Parameters and Naming Conventions

15.2 Using Formulas and Functions

CH16 Digging Deeper into DAX

16.1 Working with Variables

16.2 Writing DAX Formulas

16.3 Best Practices for DAX Coding and Debugging in Power BI

CH17 Sharing and the Power BI Workspace

17.1 Working Together in a Workspace

17.2 Creating and Configuring Apps

17.3 Slicing and Dicing Data

17.4 Troubleshooting the Use of Data Lineage

17.5 Datasets, Dataflows, and Lineage

17.6 Defending Your Data Turf

Part 5: Enhancing Your Power BI Experience

CH18 Making Your Data Shine

18.1 Establishing a Schecule

18.2 Protecting the Data Fortress

18.3 Sharing the Data Love

18.4 Refreshing Data in Baby Steps

18.5 Treating Data Like Gold

18.6 Configuring for Big Data

CH19 Extending the Power BI Experience

19.1 Linking Power Platform and Power BI

19.2 Powering Up with Power Apps

19.3 Integrating OneDrive and Power BI

19.4 Collaboration, SharePoint, and Power BI

19.5 Automating Workflows with Power BI

19.6 Unleashing Dynamics 365 for Data Analytics

Part 6: The Part of Tens

CH20 Two Ways to Optimize DAX Using Power BI

20.01 Focusing on Logic

20.02 Formatting Your Code

20.03 Keeping the Structure Simple (KISS)

20.04 Staying Clear of Certain Functions

20.05 Making Your Measures Meaningful

20.06 Filtering with a Purpose

20.07 Transforming Data Purposefully

20.08 Playing Hide-and-Seek with Your Columns

20.09 Using All Those Fabulous Functions

20.10 Rinse, Repeat, Recycle

CH21 Ten Ways to Make Compelling Reports Accessible and User-Friendly

21.01 Navigating the Keyboard

21.02 Having a Screen Reader As Your Companion

21.03 Standing Out with Contract

21.04 Recognizing Size Matters (with Focus Mode)

21.05 Switching between Data Tables and Visualizations

21.06 A Little Extra Text Goes a Long Way

21.07 Setting Rank and Tab Order

21.08 It’s All About Titles and Labels

21.09 Leaving Your Markets

21.10 Keeping with a Theme

Microsoft Certification

Power BI Data Analyst Associate

Skilles

Clean, Transform and Load Data in Power BI

Design a Data Model in Power BI

Add Measures to Power BI Desktop Models

Optimize a Model for Performance in Power BI

Design Power BI Reports

Enhance Power BI Report Designs for the User Experience

Perform Analytics in Power BI

Create and Manage Workspaces in Power BI

Manage Datasets in Power BI

Learning Resource

1. Get Started with Microsoft Data Analytics

2. Prepare Data for Analysis with Power BI

3. Model Data with Power BI

4. Build Power BI Visuals and Reports

5. Manage Workspaces and Datasets in Power BI

Power Platform Solution Architect Expert (PL-600)

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