Title Page Page: 2
Copyright and Credits Page: 2
Mastering Microsoft Power BI Page: 4
Dedication Page: 5
Packt Upsell Page: 6
Why subscribe? Page: 7
PacktPub.com Page: 8
Contributors Page: 9
About the author Page: 10
About the reviewer Page: 11
Packt is searching for authors like you Page: 12
Preface Page: 17
Who this book is for Page: 18
What this book covers Page: 19
To get the most out of this book Page: 20
Download the example code files Page: 21
Download the color images Page: 22
Conventions used Page: 23
Get in touch Page: 24
Reviews Page: 25
Planning Power BI Projects Page: 26
Power BI deployment modes Page: 27
Corporate BI Page: 28
Self-Service Visualization Page: 29
Self-Service BI Page: 30
Choosing a deployment mode Page: 31
Project discovery and ingestion Page: 32
Sample Power BI project template Page: 33
Sample template – Adventure Works BI Page: 34
Power BI project roles Page: 35
Dataset designer Page: 36
Report authors Page: 37
Power BI admin Page: 38
Project role collaboration Page: 39
Power BI licenses Page: 40
Power BI license scenarios Page: 41
Power BI Premium features Page: 42
Data warehouse bus matrix Page: 43
Dataset design process Page: 44
Selecting the business process Page: 45
Declaring the grain Page: 46
Identifying the dimensions Page: 47
Defining the facts Page: 48
Data profiling Page: 49
Dataset planning Page: 50
Data transformations Page: 51
Import versus DirectQuery Page: 52
Import mode Page: 53
DirectQuery mode Page: 54
Sample project analysis Page: 55
Summary Page: 56
Connecting to Sources and Transforming Data with M Page: 57
Query design per dataset mode Page: 58
Import mode dataset queries Page: 59
DirectQuery dataset queries Page: 60
Data sources Page: 61
Authentication Page: 62
Data source settings Page: 63
Privacy levels Page: 64
Power BI as a data source Page: 65
Power BI Desktop options Page: 66
Global options Page: 67
CURRENT FILE options Page: 68
SQL views Page: 69
SQL views versus M queries Page: 70
SQL view examples Page: 71
Date dimension view Page: 72
Mark As Date Table Page: 73
Product Dimension view Page: 74
Slowly-changing dimensions Page: 75
M queries Page: 76
Data Source Parameters Page: 77
Staging Queries Page: 78
DirectQuery staging Page: 79
Fact and dimension queries Page: 80
Source Reference Only Page: 81
M query summary Page: 82
Excel workbook – Annual Sales Plan Page: 83
Data types Page: 84
Item access in M Page: 85
DirectQuery report execution Page: 86
Bridge Tables Queries Page: 87
Parameter Tables Page: 88
Security Tables Page: 89
Query folding Page: 90
Partial query folding Page: 91
M Query examples Page: 92
Trailing three years filter Page: 93
Customer history column Page: 94
Derived column data types Page: 95
Product dimension integration Page: 96
R script transformation Page: 97
M editing tools Page: 98
Advanced Editor Page: 99
Visual Studio Code Page: 100
Visual Studio Page: 101
Summary Page: 102
Designing Import and DirectQuery Data Models Page: 103
Dataset layers Page: 104
Dataset objectives Page: 105
Competing objectives Page: 106
External factors Page: 107
The Data Model Page: 108
The Relationships View Page: 109
The Data View Page: 110
The Report View Page: 111
Fact tables Page: 112
Fact table columns Page: 113
Fact column data types Page: 114
Fact-to-dimension relationships Page: 115
Dimension tables Page: 116
Hierarchies Page: 117
Custom sort Page: 118
Bridge tables Page: 119
Parameter tables Page: 120
Measure groups Page: 121
Last refreshed date Page: 122
Measure support logic Page: 123
Relationships Page: 124
Uniqueness Page: 125
Ambiguity Page: 126
Single-direction relationships Page: 127
Direct flights only Page: 128
Bidirectional relationships Page: 129
Shared dimensions Page: 130
Date dimensions Page: 131
The CROSSFILTER function Page: 132
Model metadata Page: 133
Visibility Page: 134
Column metadata Page: 135
Default Summarization Page: 136
Data format Page: 137
Data category Page: 138
Field descriptions Page: 139
Optimizing performance Page: 140
Import Page: 141
Columnar compression Page: 142
Memory analysis via DMVs Page: 143
DirectQuery Page: 144
Optimized DAX functions Page: 145
Columnstore and HTAP Page: 146
Summary Page: 147
Developing DAX Measures and Security Roles Page: 148
DAX measures Page: 149
Filter context Page: 150
SQL equivalent Page: 151
Measure evaluation process Page: 152
Row context Page: 153
Scalar and table functions Page: 154
The CALCULATE() function Page: 155
Related tables Page: 156
The FILTER() function Page: 157
DAX variables Page: 158
Base measures Page: 159
Measure support expressions Page: 160
KPI Targets Page: 161
Current and prior periods Page: 162
Date intelligence metrics Page: 163
Current versus prior and growth rates Page: 164
Rolling periods Page: 165
Dimension metrics Page: 166
Missing dimensions Page: 167
Ranking metrics Page: 168
Dynamic ranking measures Page: 169
Security roles Page: 170
Dynamic row-level security Page: 171
Performance testing Page: 172
DAX Studio Page: 173
Tracing a Power BI dataset via DAX Studio Page: 174
Summary Page: 175
Creating and Formatting Power BI Reports Page: 176
Report planning Page: 177
Power BI report architecture Page: 178
Live connections to Power BI datasets Page: 179
Customizing Live connection reports Page: 180
Switching source datasets Page: 181
Visualization best practices Page: 182
Visualization anti-patterns Page: 183
Choosing the visual Page: 184
Tables versus charts Page: 185
Chart selection Page: 186
Visual interactions Page: 187
Edit interactions Page: 188
What-if parameters Page: 189
Slicers Page: 190
Slicer synchronization Page: 191
Custom slicer parameters Page: 192
Report filter scopes Page: 193
Report filter conditions Page: 194
Report and page filters Page: 195
Page filter or slicer? Page: 196
Relative date filtering Page: 197
Visual-level filtering Page: 198
Top N visual-level filters Page: 199
Visualization formatting Page: 200
Visual-level formatting Page: 201
Line and column charts Page: 202
Tooltips Page: 203
Report page tooltips Page: 204
Column and line chart conditional formatting Page: 205
Column chart conditional formatting Page: 206
Line chart conditional formatting Page: 207
Table and matrix Page: 208
Table and matrix conditional formatting Page: 209
Values as rows Page: 210
Scatter charts Page: 211
Map visuals Page: 212
Bubble map Page: 213
Filled map Page: 214
Mobile-optimized reports Page: 215
Responsive visuals Page: 216
Report design summary Page: 217
Summary Page: 218
Applying Custom Visuals, Animation, and Analytics Page: 219
Drillthrough report pages Page: 220
Custom labels and the back button Page: 221
Multi-column drillthrough Page: 222
Bookmarks Page: 223
Selection pane and the Spotlight property Page: 224
Custom report navigation Page: 225
View mode Page: 226
ArcGIS Map visual for Power BI Page: 227
ArcGIS Maps Plus subscriptions Page: 228
Waterfall chart breakdown Page: 229
Analytics pane Page: 230
Trend Line Page: 231
Forecast line Page: 232
Quick Insights Page: 233
Explain the increase/decrease Page: 234
Custom visuals Page: 235
Adding a custom visual Page: 236
Power KPI visual Page: 237
Chiclet Slicer Page: 238
Impact Bubble Chart Page: 239
Dot Plot by Maq Software Page: 240
Animation and data storytelling Page: 241
Play axis for scatter charts Page: 242
Pulse Chart Page: 243
Summary Page: 244
Designing Power BI Dashboards and Architectures Page: 245
Dashboards versus reports Page: 246
Dashboard design Page: 247
Visual selection Page: 248
Layout Page: 249
Navigation pane Page: 250
Full screen mode Page: 251
Supporting tiles Page: 252
Custom date filters Page: 253
Multi-dashboard architectures Page: 254
Single-dashboard architecture Page: 255
Multiple-dashboard architecture Page: 256
Organizational dashboard architecture Page: 257
Multiple datasets Page: 258
Dashboard tiles Page: 259
Tile details and custom links Page: 260
Images and text boxes Page: 261
SQL Server Reporting Services Page: 262
Excel workbooks Page: 263
Live report pages Page: 264
Mobile-optimized dashboards Page: 265
Summary Page: 266
Managing Application Workspaces and Content Page: 267
Application workspaces Page: 268
Workspace roles and rights Page: 269
Workspace admins Page: 270
Workspace members Page: 271
My Workspace Page: 272
Staged deployments Page: 273
Workspace datasets Page: 274
Power BI REST API Page: 275
Client application ID Page: 276
Workspace and content IDs Page: 277
PowerShell sample scripts Page: 278
Dashboard data classifications Page: 279
Version control Page: 280
OneDrive for Business version history Page: 281
Source control for M and DAX code Page: 282
Metadata management Page: 283
Field descriptions Page: 284
Creating descriptions Page: 285
View field descriptions Page: 286
Metadata reporting Page: 287
Query field descriptions Page: 288
Standard metadata reports Page: 289
Server and database parameters Page: 290
Querying the DMVs from Power BI Page: 291
Integrating and enhancing DMV data Page: 292
Metadata report pages Page: 293
Summary Page: 294
Managing the On-Premises Data Gateway Page: 295
On-premises data gateway planning Page: 296
Top gateway planning tasks Page: 297
Determining whether a gateway is needed Page: 298
Identifying where the gateway should be installed Page: 299
Defining the gateway infrastructure and hardware requirements Page: 300
On-premises data gateway versus personal mode Page: 301
Gateway clusters Page: 302
Gateway architectures Page: 303
Gateway security Page: 304
Gateway configuration Page: 305
The gateway service account Page: 306
TCP versus HTTPS mode Page: 307
Managing gateway clusters Page: 308
Gateway administrators Page: 309
Gateway data sources and users Page: 310
PowerShell support for gateway clusters Page: 311
Troubleshooting and monitoring gateways Page: 312
Restoring, migrating, and taking over a gateway Page: 313
Gateway log files Page: 314
Performance Monitor counters Page: 315
Scheduled data refresh Page: 316
DirectQuery datasets Page: 317
Single sign-on to DirectQuery sources via Kerberos Page: 318
Live connections to Analysis Services models Page: 319
Azure Analysis Services refresh Page: 320
Dashboard cache refresh Page: 321
Summary Page: 322
Deploying the Power BI Report Server Page: 323
Planning for the Power BI Report Server Page: 324
Feature differences with the Power BI service Page: 325
Parity with SQL Server Reporting Services Page: 326
Data sources and connectivity options Page: 327
Hardware and user licensing Page: 328
Pro licenses for report authors Page: 329
Alternative and hybrid deployment models Page: 330
Report Server reference topology Page: 331
Installation Page: 332
Hardware and software requirements Page: 333
Analysis Services Integrated Page: 334
Retrieve the Report Server product key Page: 335
Migrating from SQL Server Reporting Services Page: 336
Configuration Page: 337
Service Account Page: 338
Remote Report Server Database Page: 339
Office Online Server for Excel Workbooks Page: 340
Upgrade cycles Page: 341
Report Server Desktop Application Page: 342
Running desktop versions side by side Page: 343
Report Server Web Portal Page: 344
Scheduled data refresh Page: 345
Data source authentication Page: 346
Power BI mobile applications Page: 347
Report server administration Page: 348
Securing Power BI report content Page: 349
Execution logs Page: 350
Scale Power BI Report Server Page: 351
Summary Page: 352
Creating Power BI Apps and Content Distribution Page: 353
Content distribution methods Page: 354
Power BI apps Page: 355
Licensing apps Page: 356
App deployment process Page: 357
User permissions Page: 358
Publishing apps Page: 359
Installing apps Page: 360
Apps on Power BI mobile Page: 361
App updates Page: 362
Dataset-to-workspace relationship Page: 363
Self-Service BI workspace Page: 364
Self-Service content distribution Page: 365
Risks to Self-Service BI Page: 366
Sharing dashboards and reports Page: 367
Sharing scopes Page: 368
Sharing versus Power BI apps Page: 369
SharePoint Online embedding Page: 370
Custom application embedding Page: 371
Publish to web Page: 372
Data alerts Page: 373
Microsoft Flow integration Page: 374
Email Subscriptions Page: 375
Analyze in Excel Page: 376
Power BI Publisher for Excel Page: 377
Summary Page: 378
Administering Power BI for an Organization Page: 379
Data governance for Power BI Page: 380
Implementing data governance Page: 381
Azure Active Directory Page: 382
Azure AD B2B collaboration Page: 383
Licensing external users Page: 384
Conditional access policies Page: 385
Power BI Admin Portal Page: 386
Usage metrics Page: 387
Users and Audit logs Page: 388
Tenant settings Page: 389
Embed Codes Page: 390
Organizational Custom visuals Page: 391
Usage metrics reports Page: 392
Audit logs Page: 393
Audit log monitoring solutions Page: 394
Audit logs solution template Page: 395
Power BI Premium capacities Page: 396
Capacity allocation Page: 397
Create, size, and monitor capacities Page: 398
Change capacity size Page: 399
Monitor premium capacities Page: 400
App workspace assignment Page: 401
Capacity admins Page: 402
Summary Page: 403
Scaling with Premium and Analysis Services Page: 404
Power BI Premium Page: 405
Power BI Premium capabilities Page: 406
Corporate Power BI datasets Page: 407
Limitation of Corporate BI datasets – Reusability Page: 408
Premium capacity nodes Page: 409
Frontend versus backend resources Page: 410
Power BI Premium capacity allocation Page: 411
Corporate and Self-Service BI capacity Page: 412
Power BI Premium resource utilization Page: 413
Data model optimizations Page: 414
Report and visualization optimizations Page: 415
Premium capacity estimations Page: 416
Analysis Services Page: 417
Analysis Services Models versus Power BI Desktop Page: 418
Scale Page: 419
Usability Page: 420
Development and management tools Page: 421
Azure Analysis Services versus SSAS Page: 422
SSAS to Azure AS Migration Page: 423
Provision Azure Analysis Services Page: 424
Migration of Power BI Desktop to Analysis Services Page: 425
Summary Page: 426
Other Books You May Enjoy Page: 427
Leave a review - let other readers know what you think Page: 428
Design, create and manage robust Power BI solutions to gain meaningful business insights
Key Features
- Master all the dashboarding and reporting features of Microsoft Power BI
- Combine data from multiple sources, create stunning visualizations and publish your reports across multiple platforms
- A comprehensive guide with real-world use cases and examples demonstrating how you can get the best out of Microsoft Power BI
Book Description
This book is intended for business intelligence professionals responsible for the design and development of Power BI content as well as managers, architects and administrators who oversee Power BI projects and deployments. The chapters flow from the planning of a Power BI project through the development and distribution of content to the administration of Power BI for an organization.
BI developers will learn how to create sustainable and impactful Power BI datasets, reports, and dashboards. This includes connecting to data sources, shaping and enhancing source data, and developing an analytical data model. Additionally, top report and dashboard design practices are described using features such as Bookmarks and the Power KPI visual.
BI managers will learn how Power BI’s tools work together such as with the On-premises data gateway and how content can be staged and securely distributed via Apps. Additionally, both the Power BI Report Server and Power BI Premium are reviewed.
By the end of this book, you will be confident in creating effective charts, tables, reports or dashboards for any kind of data using the tools and techniques in Microsoft Power BI.
What you will learn
- Build efficient data retrieval and transformation processes with the Power Query M Language
- Design scalable, user-friendly DirectQuery and Import Data Models
- Develop visually rich, immersive, and interactive reports and dashboards
- Maintain version control and stage deployments across development, test, and production environments
- Manage and monitor the Power BI Service and the On-premises data gateway
- Develop a fully on-premise solution with the Power BI Report Server
- Scale up a Power BI solution via Power BI Premium capacity and migration to Azure Analysis Services or SQL Server Analysis Services
Who this book is for
Business Intelligence professionals and existing Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book to be useful. While understanding of the basic BI concepts is required, some exposure to Microsoft Power BI will be helpful.
