Beginning Power BI for Business Users: Learning to Turn Data into Insights(Tech Today)

Discover the utility of your organization’s data with Microsoft Power BI In Beginning Power BI for Business Users: Learning to Turn Data into Insights, accomplished data professional and business intelligence expert Paul Fuller delivers an intuitive and accessible handbook for professionals seeking to use Microsoft’s Power BI to access, analyze, understand, report, and act on the data available to their organizations. In the book, you’ll discover Power BI’s robust feature set, learn to ingest and model data, visualize and report on that data, and even use the DAX scripting language to unlock still more utility from Microsoft’s popular program. Beginning with general principles geared to readers with no or little experience with reporting or data analytics tools, the author walks you through how to manipulate common, publicly available data sources—including Excel files and relational databases. You’ll also learn to: Use the included and tested sample code to work through the helpful examples included by the author Conduct data orchestration and visualization to better understand and gain insights from your data An essential resource for business analysts and Excel power users reaching the limits of that program’s capabilities, Beginning Power BI for Business Users will also benefit data analysts who seek to prepare reports for their organizations using Microsoft’s flexible and intuitive software.

Table of Contents:
Introduction xxi Part 1: Introduction Chapter 1: Introducing Power BI 3 What Is Power BI? 3 Why Would I Use Power BI? 7 But Why? 7 Disconnected Data 8 Fixed Formulas 9 Ten Reasons Why Power BI Transforms Your Work 10 Will I Still Use Excel? 12 How Much Is this Going to Cost? 14 Where Do We Go from Here? 16 Chapter 2: From Data to Insight 17 Three Guiding Principles 17 Distinguishing Data, Information, and Knowledge 18 Follow a Consistent, Proven Method 21 Data Sources 21 Files 21 Databases 22 Online Services 23 Plan Ahead 23 Import Data 25 Prepare Data 26 Model Data 28 Report Data 29 Analyze Data 30 Use Visualizations Well 31 Three Ways to Ruin Visual Analytics 32 Use as Many Cool Gadgets as You Can Find 32 Overwhelm the User with Tons of Detail 32 Pick the Wrong Tool for the Job 34 Four Ways to Improve Visual Analytics 35 Reduce the Nondata Pixels 35 Enhance the Data Pixels 36 Conclusion 38 Part 2: Power BI Guided Walk-Throughs Chapter 3: Let’s Take a Flyover! 41 Getting Connected 41 A Quick Tour of the Power BI Service 42 Frequented Hotspots of Power BI 42 Adding Sample Content 43 Understanding the Power BI Service Interface 44 Highlighting 47 Slicers 50 Filters 52 Drill-Down 54 Dashboards 55 Drill-Through 58 Visibility 59 Show as Table 59 Sorting Visuals 60 Filtering— One More Time 61 Power BI Building Blocks 61 Flyover of Power BI Desktop 62 Navigating Power BI Desktop 63 Conclusion 65 Chapter 4: Building Your First Report 67 Connecting to a Data Source 67 Examining the Data Model 68 Exploring the Data 75 Building Your Report 85 Designing for Mobile Devices 101 Conclusion 102 Chapter 5: Preparing Data 103 GDP Data 103 Power Query Overview 105 Data Arrangement Steps 106 Rename Query 106 Remove Rows 106 Remove Columns 107 Applied Steps So Far 107 Promote Headers 108 Renaming Columns 108 Empty Values 109 Handling Aggregated Data 109 Filtering Rows 110 Unpivoting Data 110 Change Column Data Type 112 Changing Values in Columns 112 Duplicating Columns 113 Multiply by a Million 113 Removing Implicit Measures 114 Column Formatting 115 Calculated Columns 115 Add Previous Year Column 116 Hiding Columns 117 LOOKUPVALUE Function 118 DIVIDE Function 119 Visualize Our GDP Data 120 Where Are We? 121 Cleaning Messy Data 122 Handle Many-to-Many Relationships 123 Duplicate a Query 125 Split Column 125 Format Column 127 Remove Duplicates 127 Index Column 128 Merge Data 128 Applying Changes 129 Finding the Power Query Button 131 Simple Cleanup Tasks 131 Replacing Values 132 Custom Columns 133 More Cleanup 135 Cleaning Date Columns 136 Conclusion 138 Chapter 6: Modeling Data 139 Dimensional Modeling 140 Why Does This Matter? 143 Makes Sense to You 143 Cross-Business Process Analysis 144 Flexible Grouping 144 Performance for Power BI 144 Facts 145 Types of Facts 146 Granularity 146 Relationships Between Facts (Never!) 147 Dimensions 148 Using Integer Keys for Relationships 149 Hierarchies in Dimensions 149 Date Dimensions 150 Power Query and Data Modeling 151 How to Build a Date Dimension 152 Import a Date Table from SQL Server Database 153 Create a Date Dimension with Power Query 155 Create a Date Dimension with DAX 158 Sort by Column 161 Mark It as a Date Table 161 How to Arrange into a Star- Schema 161 Create a State Dimension 162 Create a GDP Category Dimension 163 Add a New StateID Foreign Key to Our Fact Table 163 Unpivot the GDP Year Values 164 Putting It All into Action 166 Conclusion 167 Part 3: Going Deeper Into Power BI Chapter 7: Relationships and Filtering 171 Filtering Through Relationships 171 Visuals Interact Independently 174 The Direction of Relationships 176 Bidirectional Filtering 179 Report Filter Types 181 Visual Filters 181 Date Filtering 182 Numeric Filtering 182 Text Filtering 183 Page and Report Filters 185 Controlling the Use of Filters 185 Conclusion 186 Chapter 8: Enhancing Your Report 187 Configuring Drill- Down 187 Configuring Drill- Through 190 Buttons 193 Bookmarks 195 Personal Bookmarks vs. Report Bookmarks 199 Selections and Visibility 201 Conclusion 205 Chapter 9: Refreshing, Sharing, and Collaborating 207 Refreshing Data 207 Configuring Data Source Credentials 210 Power BI Data Gateway 213 Scheduling Refresh 214 Dataset Modes 216 Sharing and Collaborating 216 Workspaces 216 Creating Workspaces 217 Publishing 217 Security and Permission Levels 219 Power BI Apps 223 Sharing 230 Summary 232 Chapter 10: Introducing Dax 233 Setup 233 Calculated Columns 235 How to Create a Calculated Column 236 DAX Measures 240 COUNTROWS and DISTINCTCOUNT 244 Filter Context 246 CALCULATE Function 249 Conclusion 250 Chapter 11: Conclusion 251 Where Does My Organization Begin? 251 Delivery Strategy 251 Business-Led Self-Service 252 IT-Managed Self-Service 253 Corporate BI 253 Which Delivery Strategy Is Right for My Organization? 253 Where Do I Go from Here? 254 Top Gurus 254 Advice 254 Index 257

About the Author :
PAUL D. FULLER has over 25 years’ experience in app development, business intelligence, and data warehousing. He offers technical leadership and delivery oversight for complex and challenging data platform projects. He is an expert in Power BI, dimensional data modeling, and data warehousing.