Jessica M. Moss
Applied Microsoft Business Intelligence
By LeBlanc, Patrick; Moss, Jessica M; Sarka, Dejan et al.
Schade – dieser Artikel ist leider ausverkauft. Sobald wir wissen, ob und wann der Artikel wieder verfügbar ist, informieren wir Sie an dieser Stelle.
Jessica M. Moss
Applied Microsoft Business Intelligence
By LeBlanc, Patrick; Moss, Jessica M; Sarka, Dejan et al.
- Broschiertes Buch
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Leverage the integration of SQL Server and Office for more effective BI
Applied Microsoft Business Intelligence shows you how to leverage the complete set of Microsoft tools--including Microsoft Office and SQL Server--to better analyze business data.
This book provides best practices for building complete BI solutions using the full Microsoft toolset. You will learn how to effectively use SQL Server Analysis and Reporting Services, along with Excel, SharePoint, and other tools to provide effective and cohesive solutions for the enterprise. Coverage includes BI architecture, data queries,…mehr
Andere Kunden interessierten sich auch für
- Richard BrathGraph Analysis and Visualization52,99 €
- Boris LublinskyProfessional Hadoop Solutions52,99 €
- Paulraj PonniahData Warehousing Fundamentals for It Professionals160,99 €
- Tom CarpenterMicrosoft SQL Server 2012 Administration57,99 €
- Gabor SzaboSocial Media Data Mining and Analytics37,99 €
- Ralph KimballThe Data Warehouse Toolkit58,99 €
- Zhe ChenData Mining and Uncertain Reasoning183,99 €
-
-
-
Leverage the integration of SQL Server and Office for more effective BI
Applied Microsoft Business Intelligence shows you how to leverage the complete set of Microsoft tools--including Microsoft Office and SQL Server--to better analyze business data.
This book provides best practices for building complete BI solutions using the full Microsoft toolset. You will learn how to effectively use SQL Server Analysis and Reporting Services, along with Excel, SharePoint, and other tools to provide effective and cohesive solutions for the enterprise. Coverage includes BI architecture, data queries, semantic models, multidimensional modeling, data analysis and visualization, performance monitoring, data mining, and more, to help you learn to perform practical business analysis and reporting. Written by an author team that includes a key member of the BI product team at Microsoft, this useful reference provides expert instruction for more effective use of the Microsoft BI toolset.
* Use Microsoft BI suite cohesively for more effective enterprise solutions
* Search, analyze, and visualize data more efficiently and completely
* Develop flexible and scalable tabular and multidimensional models
Monitor performance, build a BI portal, and deploy and manage the BI Solution
Applied Microsoft Business Intelligence shows you how to leverage the complete set of Microsoft tools--including Microsoft Office and SQL Server--to better analyze business data.
This book provides best practices for building complete BI solutions using the full Microsoft toolset. You will learn how to effectively use SQL Server Analysis and Reporting Services, along with Excel, SharePoint, and other tools to provide effective and cohesive solutions for the enterprise. Coverage includes BI architecture, data queries, semantic models, multidimensional modeling, data analysis and visualization, performance monitoring, data mining, and more, to help you learn to perform practical business analysis and reporting. Written by an author team that includes a key member of the BI product team at Microsoft, this useful reference provides expert instruction for more effective use of the Microsoft BI toolset.
* Use Microsoft BI suite cohesively for more effective enterprise solutions
* Search, analyze, and visualize data more efficiently and completely
* Develop flexible and scalable tabular and multidimensional models
Monitor performance, build a BI portal, and deploy and manage the BI Solution
Produktdetails
- Produktdetails
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 1W118961770
- Seitenzahl: 432
- Erscheinungstermin: 26. Mai 2015
- Englisch
- Abmessung: 237mm x 189mm x 22mm
- Gewicht: 745g
- ISBN-13: 9781118961773
- ISBN-10: 1118961773
- Artikelnr.: 41416424
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 1W118961770
- Seitenzahl: 432
- Erscheinungstermin: 26. Mai 2015
- Englisch
- Abmessung: 237mm x 189mm x 22mm
- Gewicht: 745g
- ISBN-13: 9781118961773
- ISBN-10: 1118961773
- Artikelnr.: 41416424
Patrick LeBlanc is a Microsoft SQL Server and Business Intelligence Technical Solution Professional. He holds a Masters of Science from Louisiana State University and has authored four SQL Server books. Jessica M. Moss, a Microsoft SQL Server MVP, is a well-known practitioner, author, and speaker in Microsoft SQL Server business intelligence. She has created numerous data warehousing solutions for companies in the retail, internet, health services, finance, and energy industries. Dejan Sarka, MCT and SQL Server MVP, focuses on development of database and business intelligence applications. He is the founder of the Slovenian SQL Server and .NET Users Group. Dustin Ryan, a Senior Business Intelligence Consultant and Trainer at Pragmatic Works, is a blogger, speaker, and author in the Microsoft SQL Server Business Intelligence field. He has developed enterprise business intelligence solutions and provided training for customers in the retail, finance, transportation, healthcare, energy, and manufacturing industries.
Introduction xiii Part I Overview of the Microsoft Business Intelligence
Toolset 1 Chapter 1 Which Analysis and Reporting Tools Do You Need? 3
Selecting a SQL Server Database Engine 4 Building a Data Warehouse 4
Selecting an RDBMS 5 Selecting SQL Server Analysis Services 6 Working with
SQL Server Reporting Services 7 Understanding Operational Reports 8
Understanding Ad Hoc Reporting 10 Working with SharePoint 11 Working with
Performance Point 12 Using Excel for Business Intelligence 14 What Is Power
Query? 14 What Is Power Pivot? 14 What Is Power View? 14 Power Map 15 Which
Development Tools Do You Need? 16 Using SQL Server Data Tools 16 Using SQL
Management Studio 17 Using Dashboard Designer 18 Using Report Builder 19
Summary 20 Chapter 2 Designing an Eff ective Business Intelligence
Architecture 21 Identifying the Audience and Goal of the Business
Intelligence Solution 21 Who's the Audience? 22 What Is the Goal(s)? 23
What Are the Data Sources? 23 Using Internal Data Sources 23 Using External
Data Sources 24 Using a Data Warehouse (or Not) 24 Implementing and
Enforcing Data Governance 26 Planning an Analytical Model 28 Planning the
Business Intelligence Delivery Solution 29 Considering Performance 30
Considering Availability 31 Summary 32 Chapter 3 Selecting the Data
Architecture that Fits Your Organization 33 Why Is Data Architecture
Selection Important? 34 Challenges 34 Benefits 35 How Do You Pick the Right
Data Architecture? 36 Understanding Architecture Options 36 Understanding
Research Selection Factors 42 Interviewing Key Stakeholders 44 Completing
the Selection Form 45 Finalizing and Approving the Architecture 46 Summary
48 Part II Business Intelligence for Analysis 49 Chapter 4 Searching and
Combining Data with Power Query 51 Downloading and Installing Power Query
52 Importing Data 56 Importing from a Database 57 Importing from the Web 59
Importing from a File 61 Transforming Data 62 Combining Data from Multiple
Sources 62 Splitting Data 64 Aggregating Data 66 Introducing M Programming
70 A Glance at the M Language 70 Adding and Removing Columns Using M 72
Summary 72 Chapter 5 Choosing the Right Business Intelligence Semantic
Model 73 Understanding the Business Intelligence Semantic Model
Architecture 74 Understanding the Data Access Layer 75 Using Power Pivot 77
Using the Multidimensional Model 78 Using the Tabular Model 78 Implementing
Query Languages and the Business Logic Layer 79 Data Analytics Expressions
(DAX) 79 Multidimensional Expressions (MDX) 81 Direct Query and ROLAP 81
Data Model Layer 82 Comparing the Different Types of Models 83 Which Model
Fits Your Organization? 84 Departmental 84 Team 86 Organizational 87
Summary 88 Chapter 6 Discovering and Analyzing Data with Power Pivot 89
Understanding Hardware and Software Requirements 90 Enabling Power Pivot 90
Designing an Optimal Power Pivot Model 92 Importing Only What You Need 92
Understanding Why Data Types Matter 99 Working with Columns or DAX
Calculated Measures 103 Optimizing the Power Pivot Model for Reporting 104
Understanding Power Pivot Model Basics 104 Adding All Necessary
Relationships 107 Adding Calculated Columns and DAX Measures 114 Creating
Hierarchies and Key Performance Indicators (KPIs) 118 Sorting Your Data to
Meet End-User Needs 121 Implementing Role-Playing Dimensions 122 Summary
125 Chapter 7 Developing a Flexible and Scalable Tabular Model 127 Why Use
a Tabular Model? 127 Understanding the Tabular Model 128 Using the Tabular
Model 128 Comparing the Tabular and Multidimensional Models 130
Understanding the Tabular Development Process 130 How Do You Design the
Model? 131 Importing Data 131 Designing Relationships 134 Calculated
Columns and Measures 135 How Do You Enhance the Model? 137 Adding
Hierarchies 137 Designing Perspectives 140 Adding Partitions 141 How Do You
Tune the Model? 144 Optimizing Processing 144 Optimizing Querying 147
Summary 149 Chapter 8 Developing a Flexible and Scalable Multidimensional
Model 151 Why Use a Multidimensional Model? 151 Understanding the
Multidimensional Model 152 Understanding the Multidimensional Model Process
153 How Do You Design the Model? 153 Creating Data Sources and the Data
Source View 153 Using the Cube Creation Wizard 156 Adjusting Measures 159
Completing Dimensions 160 How Do You Enhance the Model? 162 Adding
Navigation with Hierarchies 162 Using the Business Intelligence Wizard for
Calculations 164 Using Partitions and Aggregations 166 How Do You Tune the
Model? 169 Resolving Processing Issues 169 Querying 171 Summary 172 Chapter
9 Discovering Knowledge with Data Mining 173 Understanding the Business
Value of Data Mining 174 Understanding Data Mining Techniques 174 Common
Business Use Cases 175 Driving Decisions, Strategies, and Processes Through
Data Mining 176 Getting the Basics Right 179 Understanding the Data 180
Training and Test Datasets 182 Defining the Data Mining Structure 184 The
Data Mining Model 184 Applying the Microsoft Data Mining Techniques with
Best Practices 185 Using Microsoft Association Rules 186 Grouping Data with
Microsoft Clustering 190 Building Mining Models with Microsoft Naïve Bayes
192 Using the Microsoft Decision Trees 193 Using Microsoft Neural Network
and Microsoft Logistic Regression 195 Using Microsoft Linear Regression and
Microsoft Regression Trees 197 Microsoft Sequence Clustering 199
Forecasting with Microsoft Time Series 200 Developing and Deploying a
Scalable and Extensible Data Mining Solution 201 Choosing Between a
Relational or a Cube Source for Your Data Mining Structure 202 Deploying
Data Mining Models 202 Using DMX to Query Data Mining Models 204
Maintaining Data Mining Models 205 Fine-Tuning the Data Mining Structure
205 Keeping the Data Model Relevant 205 Continuous Learning Cycle 205
Integrating Data Mining with Your BI Solution 206 Integrating Data Mining
in Your DW and ETL Processes 206 Integrating Data Mining with Reporting
Services 207 Data Mining in Excel 207 Summary 208 Part III Business
Intelligence for Reporting 209 Chapter 10 Choosing the Right Business
Intelligence Visualization Tool 211 Why Do You Need to Choose? 211
Identifying Users 212 Selecting Tools 213 What Are the Selection Criteria?
213 Business Capabilities 214 Technical Capabilities 214 How Do You Gather
the Necessary Information? 215 What Are the Business Intelligence
Visualization Options? 215 Using SQL Server Reporting Services 215 Using
Power View 218 Using Power Map 219 How Do You Create and Complete the
Evaluation Matrix? 221 How Do You Verify and Complete the Process? 223
Evaluation Matrix #1 224 Evaluation Matrix #2 224 Summary 225 Chapter 11
Designing Operational Reports with Reporting Services 227 What Are
Operational Reports and Reporting Services? 227 Understanding Analytical
versus Operational Reports 228 Using Reporting Services 228 What Are
Development Best Practices? 230 Using Source and Version Control 231 Using
Shared Data Sources and Datasets 234 Creating Templates 236 What Are
Performance Best Practices? 237 Investigating Performance 237 Performance
Tuning 238 What Are Functionality Best Practices? 239 Using Visualizations
239 Using Filters and Parameters 240 Providing Drilldown and Drillthrough
241 Summary 244 Chapter 12 Visualizing Your Data Interactively with Power
View 245 Where Does Power View Fit with Your Reporting Solution? 246 Power
View System Requirements 246 Creating Power View Data Source Connections
247 Creating Data Sources Inside Excel 247 Creating Data Sources Inside
SharePoint 249 Creating Power View Reports 251 Using SharePoint to Create
Power View Reports 251 Using Multiple Views in Power View 252 Creating
Power View Visualizations 253 Creating Tables 253 Converting Visualizations
254 Creating Matrices 255 Creating Charts 256 Creating Multiples 261
Creating Cards 261 Creating Maps 262 Using Excel to Create Power View
Reports 263 Filtering Data with Power View 264 Adding Filters 264 Using
Advanced Filters 266 Adding Slicers 266 Invoking Cross-Filters 267 Adding
Tiles 268 Adding Filters to a Report URL 270 Exporting Power View Reports
271 Summary 272 Chapter 13 Exploring Geographic and Temporal Data with
Power Map 273 How Power Map Fits into Reporting Solutions 274 Understanding
Power Map Features and Advantages 274 Comparing Power Map to Other SQL
Server Geospatial Reporting Tools 275 Understanding Power Map Requirements
279 Optimizing Your Data Model for Power Map 280 Using Tours, Scenes, and
Layers in Power Map 280 Defining Geography Fields in Your Data Model 282
Defining Date and Time Fields in Your Data Model 283 Working with
Geospatial and Temporal Data 284 Visualizing Data Aggregation 284 Creating
a Power Map Tour 285 Visualizing Data Over Time with Rich Animations 288
Deploying and Sharing Power Map Visualizations 290 Sharing Power Map Tours
291 Enhancing Power Map Deployment and Configurations in Office 365 291
Summary 292 Chapter 14 Monitoring Your Business with PerformancePoint
Services 293 Where Does PerformancePoint Services Fit with Your Reporting
Solution? 294 Understanding PPS Features 295 When Is PPS the Right Choice?
298 Implementing PPS Requirements for SharePoint 300 Extending PPS
Dashboards 301 Adding PerformancePoint Time Intelligence 301 Using
Interactivity Features 304 Adding Reporting Services Reports to
PerformancePoint 311 Extending Filters and KPIs 313 Deployment Best
Practices 317 Following Best Practices for PerformancePoint Data
Connections and Content Libraries 317 Deploying Dashboards Across Dev,
Test, and Production Environments 319 Customizing PerformancePoint
SharePoint Web Parts 321 Security and Configuration Best Practices 325
Configuring the Unattended Service Account in SharePoint 325 Optimizing
PerformancePoint Services Application Settings 326 Summary 328 Part IV
Deploying and Managing the Business Intelligence Solution 329 Chapter 15
Implementing a Self-Service Delivery Framework 331 Planning a Self-Service
Delivery Framework 331 Creating a Data Governance Plan for Enterprise,
Team, and Personal BI 332 Identifying Stakeholders, Subject Matter Experts,
and Data Stewards 334 Understanding Industry Compliance Considerations 334
Managing Data Quality and Master Data 337 Identifying Target Audience and
Roles 339 Developing a Training Plan 340 Inventorying Tools and Skillset
340 Understanding Data Quality Services 340 Understanding Master Data
Services 342 Managing Data Quality and Master Data in Excel 345 Business
Intelligence Features Across the Microsoft Data Platform Versions and
Editions 347 Defining Success Criteria 348 Summary 349 Chapter 16 Designing
and Implementing a Deployment Plan 351 What Is a Deployment Plan? 351 How
Do You Deploy Business Intelligence Code? 353 Using Analysis Services
(Multidimensional or Tabular) 354 Using Reporting Services 357 How Do You
Implement the Deployment Plan? 359 Planning the Deployment 359 Designing
Scripts 360 Documenting Steps 360 Testing the Plan 361 Training Your Staff
362 Summary 362 Chapter 17 Managing and Maintaining the Business
Intelligence Environment 363 Using SQL Server Reporting Services 363
Configuring Memory 365 Caching Data and Pre-Rendering Reports 368 Using
ExecutionLog Views 369 Working with SQL Server Analysis Services 372 Using
Multidimensional Models 372 Using Tabular Models 374 Using SharePoint to
Improve Performance 375 Summary 378 Chapter 18 Scaling the Business
Intelligence Environment 379 Why Would You Scale the Business Intelligence
Environment? 379 How Do You Scale Each Tool? 381 Using Analysis Services
(Multidimensional or Tabular) 381 Reporting Services 385 Using Power Pivot
and Power View 387 Summary 390 Index 391
Toolset 1 Chapter 1 Which Analysis and Reporting Tools Do You Need? 3
Selecting a SQL Server Database Engine 4 Building a Data Warehouse 4
Selecting an RDBMS 5 Selecting SQL Server Analysis Services 6 Working with
SQL Server Reporting Services 7 Understanding Operational Reports 8
Understanding Ad Hoc Reporting 10 Working with SharePoint 11 Working with
Performance Point 12 Using Excel for Business Intelligence 14 What Is Power
Query? 14 What Is Power Pivot? 14 What Is Power View? 14 Power Map 15 Which
Development Tools Do You Need? 16 Using SQL Server Data Tools 16 Using SQL
Management Studio 17 Using Dashboard Designer 18 Using Report Builder 19
Summary 20 Chapter 2 Designing an Eff ective Business Intelligence
Architecture 21 Identifying the Audience and Goal of the Business
Intelligence Solution 21 Who's the Audience? 22 What Is the Goal(s)? 23
What Are the Data Sources? 23 Using Internal Data Sources 23 Using External
Data Sources 24 Using a Data Warehouse (or Not) 24 Implementing and
Enforcing Data Governance 26 Planning an Analytical Model 28 Planning the
Business Intelligence Delivery Solution 29 Considering Performance 30
Considering Availability 31 Summary 32 Chapter 3 Selecting the Data
Architecture that Fits Your Organization 33 Why Is Data Architecture
Selection Important? 34 Challenges 34 Benefits 35 How Do You Pick the Right
Data Architecture? 36 Understanding Architecture Options 36 Understanding
Research Selection Factors 42 Interviewing Key Stakeholders 44 Completing
the Selection Form 45 Finalizing and Approving the Architecture 46 Summary
48 Part II Business Intelligence for Analysis 49 Chapter 4 Searching and
Combining Data with Power Query 51 Downloading and Installing Power Query
52 Importing Data 56 Importing from a Database 57 Importing from the Web 59
Importing from a File 61 Transforming Data 62 Combining Data from Multiple
Sources 62 Splitting Data 64 Aggregating Data 66 Introducing M Programming
70 A Glance at the M Language 70 Adding and Removing Columns Using M 72
Summary 72 Chapter 5 Choosing the Right Business Intelligence Semantic
Model 73 Understanding the Business Intelligence Semantic Model
Architecture 74 Understanding the Data Access Layer 75 Using Power Pivot 77
Using the Multidimensional Model 78 Using the Tabular Model 78 Implementing
Query Languages and the Business Logic Layer 79 Data Analytics Expressions
(DAX) 79 Multidimensional Expressions (MDX) 81 Direct Query and ROLAP 81
Data Model Layer 82 Comparing the Different Types of Models 83 Which Model
Fits Your Organization? 84 Departmental 84 Team 86 Organizational 87
Summary 88 Chapter 6 Discovering and Analyzing Data with Power Pivot 89
Understanding Hardware and Software Requirements 90 Enabling Power Pivot 90
Designing an Optimal Power Pivot Model 92 Importing Only What You Need 92
Understanding Why Data Types Matter 99 Working with Columns or DAX
Calculated Measures 103 Optimizing the Power Pivot Model for Reporting 104
Understanding Power Pivot Model Basics 104 Adding All Necessary
Relationships 107 Adding Calculated Columns and DAX Measures 114 Creating
Hierarchies and Key Performance Indicators (KPIs) 118 Sorting Your Data to
Meet End-User Needs 121 Implementing Role-Playing Dimensions 122 Summary
125 Chapter 7 Developing a Flexible and Scalable Tabular Model 127 Why Use
a Tabular Model? 127 Understanding the Tabular Model 128 Using the Tabular
Model 128 Comparing the Tabular and Multidimensional Models 130
Understanding the Tabular Development Process 130 How Do You Design the
Model? 131 Importing Data 131 Designing Relationships 134 Calculated
Columns and Measures 135 How Do You Enhance the Model? 137 Adding
Hierarchies 137 Designing Perspectives 140 Adding Partitions 141 How Do You
Tune the Model? 144 Optimizing Processing 144 Optimizing Querying 147
Summary 149 Chapter 8 Developing a Flexible and Scalable Multidimensional
Model 151 Why Use a Multidimensional Model? 151 Understanding the
Multidimensional Model 152 Understanding the Multidimensional Model Process
153 How Do You Design the Model? 153 Creating Data Sources and the Data
Source View 153 Using the Cube Creation Wizard 156 Adjusting Measures 159
Completing Dimensions 160 How Do You Enhance the Model? 162 Adding
Navigation with Hierarchies 162 Using the Business Intelligence Wizard for
Calculations 164 Using Partitions and Aggregations 166 How Do You Tune the
Model? 169 Resolving Processing Issues 169 Querying 171 Summary 172 Chapter
9 Discovering Knowledge with Data Mining 173 Understanding the Business
Value of Data Mining 174 Understanding Data Mining Techniques 174 Common
Business Use Cases 175 Driving Decisions, Strategies, and Processes Through
Data Mining 176 Getting the Basics Right 179 Understanding the Data 180
Training and Test Datasets 182 Defining the Data Mining Structure 184 The
Data Mining Model 184 Applying the Microsoft Data Mining Techniques with
Best Practices 185 Using Microsoft Association Rules 186 Grouping Data with
Microsoft Clustering 190 Building Mining Models with Microsoft Naïve Bayes
192 Using the Microsoft Decision Trees 193 Using Microsoft Neural Network
and Microsoft Logistic Regression 195 Using Microsoft Linear Regression and
Microsoft Regression Trees 197 Microsoft Sequence Clustering 199
Forecasting with Microsoft Time Series 200 Developing and Deploying a
Scalable and Extensible Data Mining Solution 201 Choosing Between a
Relational or a Cube Source for Your Data Mining Structure 202 Deploying
Data Mining Models 202 Using DMX to Query Data Mining Models 204
Maintaining Data Mining Models 205 Fine-Tuning the Data Mining Structure
205 Keeping the Data Model Relevant 205 Continuous Learning Cycle 205
Integrating Data Mining with Your BI Solution 206 Integrating Data Mining
in Your DW and ETL Processes 206 Integrating Data Mining with Reporting
Services 207 Data Mining in Excel 207 Summary 208 Part III Business
Intelligence for Reporting 209 Chapter 10 Choosing the Right Business
Intelligence Visualization Tool 211 Why Do You Need to Choose? 211
Identifying Users 212 Selecting Tools 213 What Are the Selection Criteria?
213 Business Capabilities 214 Technical Capabilities 214 How Do You Gather
the Necessary Information? 215 What Are the Business Intelligence
Visualization Options? 215 Using SQL Server Reporting Services 215 Using
Power View 218 Using Power Map 219 How Do You Create and Complete the
Evaluation Matrix? 221 How Do You Verify and Complete the Process? 223
Evaluation Matrix #1 224 Evaluation Matrix #2 224 Summary 225 Chapter 11
Designing Operational Reports with Reporting Services 227 What Are
Operational Reports and Reporting Services? 227 Understanding Analytical
versus Operational Reports 228 Using Reporting Services 228 What Are
Development Best Practices? 230 Using Source and Version Control 231 Using
Shared Data Sources and Datasets 234 Creating Templates 236 What Are
Performance Best Practices? 237 Investigating Performance 237 Performance
Tuning 238 What Are Functionality Best Practices? 239 Using Visualizations
239 Using Filters and Parameters 240 Providing Drilldown and Drillthrough
241 Summary 244 Chapter 12 Visualizing Your Data Interactively with Power
View 245 Where Does Power View Fit with Your Reporting Solution? 246 Power
View System Requirements 246 Creating Power View Data Source Connections
247 Creating Data Sources Inside Excel 247 Creating Data Sources Inside
SharePoint 249 Creating Power View Reports 251 Using SharePoint to Create
Power View Reports 251 Using Multiple Views in Power View 252 Creating
Power View Visualizations 253 Creating Tables 253 Converting Visualizations
254 Creating Matrices 255 Creating Charts 256 Creating Multiples 261
Creating Cards 261 Creating Maps 262 Using Excel to Create Power View
Reports 263 Filtering Data with Power View 264 Adding Filters 264 Using
Advanced Filters 266 Adding Slicers 266 Invoking Cross-Filters 267 Adding
Tiles 268 Adding Filters to a Report URL 270 Exporting Power View Reports
271 Summary 272 Chapter 13 Exploring Geographic and Temporal Data with
Power Map 273 How Power Map Fits into Reporting Solutions 274 Understanding
Power Map Features and Advantages 274 Comparing Power Map to Other SQL
Server Geospatial Reporting Tools 275 Understanding Power Map Requirements
279 Optimizing Your Data Model for Power Map 280 Using Tours, Scenes, and
Layers in Power Map 280 Defining Geography Fields in Your Data Model 282
Defining Date and Time Fields in Your Data Model 283 Working with
Geospatial and Temporal Data 284 Visualizing Data Aggregation 284 Creating
a Power Map Tour 285 Visualizing Data Over Time with Rich Animations 288
Deploying and Sharing Power Map Visualizations 290 Sharing Power Map Tours
291 Enhancing Power Map Deployment and Configurations in Office 365 291
Summary 292 Chapter 14 Monitoring Your Business with PerformancePoint
Services 293 Where Does PerformancePoint Services Fit with Your Reporting
Solution? 294 Understanding PPS Features 295 When Is PPS the Right Choice?
298 Implementing PPS Requirements for SharePoint 300 Extending PPS
Dashboards 301 Adding PerformancePoint Time Intelligence 301 Using
Interactivity Features 304 Adding Reporting Services Reports to
PerformancePoint 311 Extending Filters and KPIs 313 Deployment Best
Practices 317 Following Best Practices for PerformancePoint Data
Connections and Content Libraries 317 Deploying Dashboards Across Dev,
Test, and Production Environments 319 Customizing PerformancePoint
SharePoint Web Parts 321 Security and Configuration Best Practices 325
Configuring the Unattended Service Account in SharePoint 325 Optimizing
PerformancePoint Services Application Settings 326 Summary 328 Part IV
Deploying and Managing the Business Intelligence Solution 329 Chapter 15
Implementing a Self-Service Delivery Framework 331 Planning a Self-Service
Delivery Framework 331 Creating a Data Governance Plan for Enterprise,
Team, and Personal BI 332 Identifying Stakeholders, Subject Matter Experts,
and Data Stewards 334 Understanding Industry Compliance Considerations 334
Managing Data Quality and Master Data 337 Identifying Target Audience and
Roles 339 Developing a Training Plan 340 Inventorying Tools and Skillset
340 Understanding Data Quality Services 340 Understanding Master Data
Services 342 Managing Data Quality and Master Data in Excel 345 Business
Intelligence Features Across the Microsoft Data Platform Versions and
Editions 347 Defining Success Criteria 348 Summary 349 Chapter 16 Designing
and Implementing a Deployment Plan 351 What Is a Deployment Plan? 351 How
Do You Deploy Business Intelligence Code? 353 Using Analysis Services
(Multidimensional or Tabular) 354 Using Reporting Services 357 How Do You
Implement the Deployment Plan? 359 Planning the Deployment 359 Designing
Scripts 360 Documenting Steps 360 Testing the Plan 361 Training Your Staff
362 Summary 362 Chapter 17 Managing and Maintaining the Business
Intelligence Environment 363 Using SQL Server Reporting Services 363
Configuring Memory 365 Caching Data and Pre-Rendering Reports 368 Using
ExecutionLog Views 369 Working with SQL Server Analysis Services 372 Using
Multidimensional Models 372 Using Tabular Models 374 Using SharePoint to
Improve Performance 375 Summary 378 Chapter 18 Scaling the Business
Intelligence Environment 379 Why Would You Scale the Business Intelligence
Environment? 379 How Do You Scale Each Tool? 381 Using Analysis Services
(Multidimensional or Tabular) 381 Reporting Services 385 Using Power Pivot
and Power View 387 Summary 390 Index 391
Introduction xiii Part I Overview of the Microsoft Business Intelligence
Toolset 1 Chapter 1 Which Analysis and Reporting Tools Do You Need? 3
Selecting a SQL Server Database Engine 4 Building a Data Warehouse 4
Selecting an RDBMS 5 Selecting SQL Server Analysis Services 6 Working with
SQL Server Reporting Services 7 Understanding Operational Reports 8
Understanding Ad Hoc Reporting 10 Working with SharePoint 11 Working with
Performance Point 12 Using Excel for Business Intelligence 14 What Is Power
Query? 14 What Is Power Pivot? 14 What Is Power View? 14 Power Map 15 Which
Development Tools Do You Need? 16 Using SQL Server Data Tools 16 Using SQL
Management Studio 17 Using Dashboard Designer 18 Using Report Builder 19
Summary 20 Chapter 2 Designing an Eff ective Business Intelligence
Architecture 21 Identifying the Audience and Goal of the Business
Intelligence Solution 21 Who's the Audience? 22 What Is the Goal(s)? 23
What Are the Data Sources? 23 Using Internal Data Sources 23 Using External
Data Sources 24 Using a Data Warehouse (or Not) 24 Implementing and
Enforcing Data Governance 26 Planning an Analytical Model 28 Planning the
Business Intelligence Delivery Solution 29 Considering Performance 30
Considering Availability 31 Summary 32 Chapter 3 Selecting the Data
Architecture that Fits Your Organization 33 Why Is Data Architecture
Selection Important? 34 Challenges 34 Benefits 35 How Do You Pick the Right
Data Architecture? 36 Understanding Architecture Options 36 Understanding
Research Selection Factors 42 Interviewing Key Stakeholders 44 Completing
the Selection Form 45 Finalizing and Approving the Architecture 46 Summary
48 Part II Business Intelligence for Analysis 49 Chapter 4 Searching and
Combining Data with Power Query 51 Downloading and Installing Power Query
52 Importing Data 56 Importing from a Database 57 Importing from the Web 59
Importing from a File 61 Transforming Data 62 Combining Data from Multiple
Sources 62 Splitting Data 64 Aggregating Data 66 Introducing M Programming
70 A Glance at the M Language 70 Adding and Removing Columns Using M 72
Summary 72 Chapter 5 Choosing the Right Business Intelligence Semantic
Model 73 Understanding the Business Intelligence Semantic Model
Architecture 74 Understanding the Data Access Layer 75 Using Power Pivot 77
Using the Multidimensional Model 78 Using the Tabular Model 78 Implementing
Query Languages and the Business Logic Layer 79 Data Analytics Expressions
(DAX) 79 Multidimensional Expressions (MDX) 81 Direct Query and ROLAP 81
Data Model Layer 82 Comparing the Different Types of Models 83 Which Model
Fits Your Organization? 84 Departmental 84 Team 86 Organizational 87
Summary 88 Chapter 6 Discovering and Analyzing Data with Power Pivot 89
Understanding Hardware and Software Requirements 90 Enabling Power Pivot 90
Designing an Optimal Power Pivot Model 92 Importing Only What You Need 92
Understanding Why Data Types Matter 99 Working with Columns or DAX
Calculated Measures 103 Optimizing the Power Pivot Model for Reporting 104
Understanding Power Pivot Model Basics 104 Adding All Necessary
Relationships 107 Adding Calculated Columns and DAX Measures 114 Creating
Hierarchies and Key Performance Indicators (KPIs) 118 Sorting Your Data to
Meet End-User Needs 121 Implementing Role-Playing Dimensions 122 Summary
125 Chapter 7 Developing a Flexible and Scalable Tabular Model 127 Why Use
a Tabular Model? 127 Understanding the Tabular Model 128 Using the Tabular
Model 128 Comparing the Tabular and Multidimensional Models 130
Understanding the Tabular Development Process 130 How Do You Design the
Model? 131 Importing Data 131 Designing Relationships 134 Calculated
Columns and Measures 135 How Do You Enhance the Model? 137 Adding
Hierarchies 137 Designing Perspectives 140 Adding Partitions 141 How Do You
Tune the Model? 144 Optimizing Processing 144 Optimizing Querying 147
Summary 149 Chapter 8 Developing a Flexible and Scalable Multidimensional
Model 151 Why Use a Multidimensional Model? 151 Understanding the
Multidimensional Model 152 Understanding the Multidimensional Model Process
153 How Do You Design the Model? 153 Creating Data Sources and the Data
Source View 153 Using the Cube Creation Wizard 156 Adjusting Measures 159
Completing Dimensions 160 How Do You Enhance the Model? 162 Adding
Navigation with Hierarchies 162 Using the Business Intelligence Wizard for
Calculations 164 Using Partitions and Aggregations 166 How Do You Tune the
Model? 169 Resolving Processing Issues 169 Querying 171 Summary 172 Chapter
9 Discovering Knowledge with Data Mining 173 Understanding the Business
Value of Data Mining 174 Understanding Data Mining Techniques 174 Common
Business Use Cases 175 Driving Decisions, Strategies, and Processes Through
Data Mining 176 Getting the Basics Right 179 Understanding the Data 180
Training and Test Datasets 182 Defining the Data Mining Structure 184 The
Data Mining Model 184 Applying the Microsoft Data Mining Techniques with
Best Practices 185 Using Microsoft Association Rules 186 Grouping Data with
Microsoft Clustering 190 Building Mining Models with Microsoft Naïve Bayes
192 Using the Microsoft Decision Trees 193 Using Microsoft Neural Network
and Microsoft Logistic Regression 195 Using Microsoft Linear Regression and
Microsoft Regression Trees 197 Microsoft Sequence Clustering 199
Forecasting with Microsoft Time Series 200 Developing and Deploying a
Scalable and Extensible Data Mining Solution 201 Choosing Between a
Relational or a Cube Source for Your Data Mining Structure 202 Deploying
Data Mining Models 202 Using DMX to Query Data Mining Models 204
Maintaining Data Mining Models 205 Fine-Tuning the Data Mining Structure
205 Keeping the Data Model Relevant 205 Continuous Learning Cycle 205
Integrating Data Mining with Your BI Solution 206 Integrating Data Mining
in Your DW and ETL Processes 206 Integrating Data Mining with Reporting
Services 207 Data Mining in Excel 207 Summary 208 Part III Business
Intelligence for Reporting 209 Chapter 10 Choosing the Right Business
Intelligence Visualization Tool 211 Why Do You Need to Choose? 211
Identifying Users 212 Selecting Tools 213 What Are the Selection Criteria?
213 Business Capabilities 214 Technical Capabilities 214 How Do You Gather
the Necessary Information? 215 What Are the Business Intelligence
Visualization Options? 215 Using SQL Server Reporting Services 215 Using
Power View 218 Using Power Map 219 How Do You Create and Complete the
Evaluation Matrix? 221 How Do You Verify and Complete the Process? 223
Evaluation Matrix #1 224 Evaluation Matrix #2 224 Summary 225 Chapter 11
Designing Operational Reports with Reporting Services 227 What Are
Operational Reports and Reporting Services? 227 Understanding Analytical
versus Operational Reports 228 Using Reporting Services 228 What Are
Development Best Practices? 230 Using Source and Version Control 231 Using
Shared Data Sources and Datasets 234 Creating Templates 236 What Are
Performance Best Practices? 237 Investigating Performance 237 Performance
Tuning 238 What Are Functionality Best Practices? 239 Using Visualizations
239 Using Filters and Parameters 240 Providing Drilldown and Drillthrough
241 Summary 244 Chapter 12 Visualizing Your Data Interactively with Power
View 245 Where Does Power View Fit with Your Reporting Solution? 246 Power
View System Requirements 246 Creating Power View Data Source Connections
247 Creating Data Sources Inside Excel 247 Creating Data Sources Inside
SharePoint 249 Creating Power View Reports 251 Using SharePoint to Create
Power View Reports 251 Using Multiple Views in Power View 252 Creating
Power View Visualizations 253 Creating Tables 253 Converting Visualizations
254 Creating Matrices 255 Creating Charts 256 Creating Multiples 261
Creating Cards 261 Creating Maps 262 Using Excel to Create Power View
Reports 263 Filtering Data with Power View 264 Adding Filters 264 Using
Advanced Filters 266 Adding Slicers 266 Invoking Cross-Filters 267 Adding
Tiles 268 Adding Filters to a Report URL 270 Exporting Power View Reports
271 Summary 272 Chapter 13 Exploring Geographic and Temporal Data with
Power Map 273 How Power Map Fits into Reporting Solutions 274 Understanding
Power Map Features and Advantages 274 Comparing Power Map to Other SQL
Server Geospatial Reporting Tools 275 Understanding Power Map Requirements
279 Optimizing Your Data Model for Power Map 280 Using Tours, Scenes, and
Layers in Power Map 280 Defining Geography Fields in Your Data Model 282
Defining Date and Time Fields in Your Data Model 283 Working with
Geospatial and Temporal Data 284 Visualizing Data Aggregation 284 Creating
a Power Map Tour 285 Visualizing Data Over Time with Rich Animations 288
Deploying and Sharing Power Map Visualizations 290 Sharing Power Map Tours
291 Enhancing Power Map Deployment and Configurations in Office 365 291
Summary 292 Chapter 14 Monitoring Your Business with PerformancePoint
Services 293 Where Does PerformancePoint Services Fit with Your Reporting
Solution? 294 Understanding PPS Features 295 When Is PPS the Right Choice?
298 Implementing PPS Requirements for SharePoint 300 Extending PPS
Dashboards 301 Adding PerformancePoint Time Intelligence 301 Using
Interactivity Features 304 Adding Reporting Services Reports to
PerformancePoint 311 Extending Filters and KPIs 313 Deployment Best
Practices 317 Following Best Practices for PerformancePoint Data
Connections and Content Libraries 317 Deploying Dashboards Across Dev,
Test, and Production Environments 319 Customizing PerformancePoint
SharePoint Web Parts 321 Security and Configuration Best Practices 325
Configuring the Unattended Service Account in SharePoint 325 Optimizing
PerformancePoint Services Application Settings 326 Summary 328 Part IV
Deploying and Managing the Business Intelligence Solution 329 Chapter 15
Implementing a Self-Service Delivery Framework 331 Planning a Self-Service
Delivery Framework 331 Creating a Data Governance Plan for Enterprise,
Team, and Personal BI 332 Identifying Stakeholders, Subject Matter Experts,
and Data Stewards 334 Understanding Industry Compliance Considerations 334
Managing Data Quality and Master Data 337 Identifying Target Audience and
Roles 339 Developing a Training Plan 340 Inventorying Tools and Skillset
340 Understanding Data Quality Services 340 Understanding Master Data
Services 342 Managing Data Quality and Master Data in Excel 345 Business
Intelligence Features Across the Microsoft Data Platform Versions and
Editions 347 Defining Success Criteria 348 Summary 349 Chapter 16 Designing
and Implementing a Deployment Plan 351 What Is a Deployment Plan? 351 How
Do You Deploy Business Intelligence Code? 353 Using Analysis Services
(Multidimensional or Tabular) 354 Using Reporting Services 357 How Do You
Implement the Deployment Plan? 359 Planning the Deployment 359 Designing
Scripts 360 Documenting Steps 360 Testing the Plan 361 Training Your Staff
362 Summary 362 Chapter 17 Managing and Maintaining the Business
Intelligence Environment 363 Using SQL Server Reporting Services 363
Configuring Memory 365 Caching Data and Pre-Rendering Reports 368 Using
ExecutionLog Views 369 Working with SQL Server Analysis Services 372 Using
Multidimensional Models 372 Using Tabular Models 374 Using SharePoint to
Improve Performance 375 Summary 378 Chapter 18 Scaling the Business
Intelligence Environment 379 Why Would You Scale the Business Intelligence
Environment? 379 How Do You Scale Each Tool? 381 Using Analysis Services
(Multidimensional or Tabular) 381 Reporting Services 385 Using Power Pivot
and Power View 387 Summary 390 Index 391
Toolset 1 Chapter 1 Which Analysis and Reporting Tools Do You Need? 3
Selecting a SQL Server Database Engine 4 Building a Data Warehouse 4
Selecting an RDBMS 5 Selecting SQL Server Analysis Services 6 Working with
SQL Server Reporting Services 7 Understanding Operational Reports 8
Understanding Ad Hoc Reporting 10 Working with SharePoint 11 Working with
Performance Point 12 Using Excel for Business Intelligence 14 What Is Power
Query? 14 What Is Power Pivot? 14 What Is Power View? 14 Power Map 15 Which
Development Tools Do You Need? 16 Using SQL Server Data Tools 16 Using SQL
Management Studio 17 Using Dashboard Designer 18 Using Report Builder 19
Summary 20 Chapter 2 Designing an Eff ective Business Intelligence
Architecture 21 Identifying the Audience and Goal of the Business
Intelligence Solution 21 Who's the Audience? 22 What Is the Goal(s)? 23
What Are the Data Sources? 23 Using Internal Data Sources 23 Using External
Data Sources 24 Using a Data Warehouse (or Not) 24 Implementing and
Enforcing Data Governance 26 Planning an Analytical Model 28 Planning the
Business Intelligence Delivery Solution 29 Considering Performance 30
Considering Availability 31 Summary 32 Chapter 3 Selecting the Data
Architecture that Fits Your Organization 33 Why Is Data Architecture
Selection Important? 34 Challenges 34 Benefits 35 How Do You Pick the Right
Data Architecture? 36 Understanding Architecture Options 36 Understanding
Research Selection Factors 42 Interviewing Key Stakeholders 44 Completing
the Selection Form 45 Finalizing and Approving the Architecture 46 Summary
48 Part II Business Intelligence for Analysis 49 Chapter 4 Searching and
Combining Data with Power Query 51 Downloading and Installing Power Query
52 Importing Data 56 Importing from a Database 57 Importing from the Web 59
Importing from a File 61 Transforming Data 62 Combining Data from Multiple
Sources 62 Splitting Data 64 Aggregating Data 66 Introducing M Programming
70 A Glance at the M Language 70 Adding and Removing Columns Using M 72
Summary 72 Chapter 5 Choosing the Right Business Intelligence Semantic
Model 73 Understanding the Business Intelligence Semantic Model
Architecture 74 Understanding the Data Access Layer 75 Using Power Pivot 77
Using the Multidimensional Model 78 Using the Tabular Model 78 Implementing
Query Languages and the Business Logic Layer 79 Data Analytics Expressions
(DAX) 79 Multidimensional Expressions (MDX) 81 Direct Query and ROLAP 81
Data Model Layer 82 Comparing the Different Types of Models 83 Which Model
Fits Your Organization? 84 Departmental 84 Team 86 Organizational 87
Summary 88 Chapter 6 Discovering and Analyzing Data with Power Pivot 89
Understanding Hardware and Software Requirements 90 Enabling Power Pivot 90
Designing an Optimal Power Pivot Model 92 Importing Only What You Need 92
Understanding Why Data Types Matter 99 Working with Columns or DAX
Calculated Measures 103 Optimizing the Power Pivot Model for Reporting 104
Understanding Power Pivot Model Basics 104 Adding All Necessary
Relationships 107 Adding Calculated Columns and DAX Measures 114 Creating
Hierarchies and Key Performance Indicators (KPIs) 118 Sorting Your Data to
Meet End-User Needs 121 Implementing Role-Playing Dimensions 122 Summary
125 Chapter 7 Developing a Flexible and Scalable Tabular Model 127 Why Use
a Tabular Model? 127 Understanding the Tabular Model 128 Using the Tabular
Model 128 Comparing the Tabular and Multidimensional Models 130
Understanding the Tabular Development Process 130 How Do You Design the
Model? 131 Importing Data 131 Designing Relationships 134 Calculated
Columns and Measures 135 How Do You Enhance the Model? 137 Adding
Hierarchies 137 Designing Perspectives 140 Adding Partitions 141 How Do You
Tune the Model? 144 Optimizing Processing 144 Optimizing Querying 147
Summary 149 Chapter 8 Developing a Flexible and Scalable Multidimensional
Model 151 Why Use a Multidimensional Model? 151 Understanding the
Multidimensional Model 152 Understanding the Multidimensional Model Process
153 How Do You Design the Model? 153 Creating Data Sources and the Data
Source View 153 Using the Cube Creation Wizard 156 Adjusting Measures 159
Completing Dimensions 160 How Do You Enhance the Model? 162 Adding
Navigation with Hierarchies 162 Using the Business Intelligence Wizard for
Calculations 164 Using Partitions and Aggregations 166 How Do You Tune the
Model? 169 Resolving Processing Issues 169 Querying 171 Summary 172 Chapter
9 Discovering Knowledge with Data Mining 173 Understanding the Business
Value of Data Mining 174 Understanding Data Mining Techniques 174 Common
Business Use Cases 175 Driving Decisions, Strategies, and Processes Through
Data Mining 176 Getting the Basics Right 179 Understanding the Data 180
Training and Test Datasets 182 Defining the Data Mining Structure 184 The
Data Mining Model 184 Applying the Microsoft Data Mining Techniques with
Best Practices 185 Using Microsoft Association Rules 186 Grouping Data with
Microsoft Clustering 190 Building Mining Models with Microsoft Naïve Bayes
192 Using the Microsoft Decision Trees 193 Using Microsoft Neural Network
and Microsoft Logistic Regression 195 Using Microsoft Linear Regression and
Microsoft Regression Trees 197 Microsoft Sequence Clustering 199
Forecasting with Microsoft Time Series 200 Developing and Deploying a
Scalable and Extensible Data Mining Solution 201 Choosing Between a
Relational or a Cube Source for Your Data Mining Structure 202 Deploying
Data Mining Models 202 Using DMX to Query Data Mining Models 204
Maintaining Data Mining Models 205 Fine-Tuning the Data Mining Structure
205 Keeping the Data Model Relevant 205 Continuous Learning Cycle 205
Integrating Data Mining with Your BI Solution 206 Integrating Data Mining
in Your DW and ETL Processes 206 Integrating Data Mining with Reporting
Services 207 Data Mining in Excel 207 Summary 208 Part III Business
Intelligence for Reporting 209 Chapter 10 Choosing the Right Business
Intelligence Visualization Tool 211 Why Do You Need to Choose? 211
Identifying Users 212 Selecting Tools 213 What Are the Selection Criteria?
213 Business Capabilities 214 Technical Capabilities 214 How Do You Gather
the Necessary Information? 215 What Are the Business Intelligence
Visualization Options? 215 Using SQL Server Reporting Services 215 Using
Power View 218 Using Power Map 219 How Do You Create and Complete the
Evaluation Matrix? 221 How Do You Verify and Complete the Process? 223
Evaluation Matrix #1 224 Evaluation Matrix #2 224 Summary 225 Chapter 11
Designing Operational Reports with Reporting Services 227 What Are
Operational Reports and Reporting Services? 227 Understanding Analytical
versus Operational Reports 228 Using Reporting Services 228 What Are
Development Best Practices? 230 Using Source and Version Control 231 Using
Shared Data Sources and Datasets 234 Creating Templates 236 What Are
Performance Best Practices? 237 Investigating Performance 237 Performance
Tuning 238 What Are Functionality Best Practices? 239 Using Visualizations
239 Using Filters and Parameters 240 Providing Drilldown and Drillthrough
241 Summary 244 Chapter 12 Visualizing Your Data Interactively with Power
View 245 Where Does Power View Fit with Your Reporting Solution? 246 Power
View System Requirements 246 Creating Power View Data Source Connections
247 Creating Data Sources Inside Excel 247 Creating Data Sources Inside
SharePoint 249 Creating Power View Reports 251 Using SharePoint to Create
Power View Reports 251 Using Multiple Views in Power View 252 Creating
Power View Visualizations 253 Creating Tables 253 Converting Visualizations
254 Creating Matrices 255 Creating Charts 256 Creating Multiples 261
Creating Cards 261 Creating Maps 262 Using Excel to Create Power View
Reports 263 Filtering Data with Power View 264 Adding Filters 264 Using
Advanced Filters 266 Adding Slicers 266 Invoking Cross-Filters 267 Adding
Tiles 268 Adding Filters to a Report URL 270 Exporting Power View Reports
271 Summary 272 Chapter 13 Exploring Geographic and Temporal Data with
Power Map 273 How Power Map Fits into Reporting Solutions 274 Understanding
Power Map Features and Advantages 274 Comparing Power Map to Other SQL
Server Geospatial Reporting Tools 275 Understanding Power Map Requirements
279 Optimizing Your Data Model for Power Map 280 Using Tours, Scenes, and
Layers in Power Map 280 Defining Geography Fields in Your Data Model 282
Defining Date and Time Fields in Your Data Model 283 Working with
Geospatial and Temporal Data 284 Visualizing Data Aggregation 284 Creating
a Power Map Tour 285 Visualizing Data Over Time with Rich Animations 288
Deploying and Sharing Power Map Visualizations 290 Sharing Power Map Tours
291 Enhancing Power Map Deployment and Configurations in Office 365 291
Summary 292 Chapter 14 Monitoring Your Business with PerformancePoint
Services 293 Where Does PerformancePoint Services Fit with Your Reporting
Solution? 294 Understanding PPS Features 295 When Is PPS the Right Choice?
298 Implementing PPS Requirements for SharePoint 300 Extending PPS
Dashboards 301 Adding PerformancePoint Time Intelligence 301 Using
Interactivity Features 304 Adding Reporting Services Reports to
PerformancePoint 311 Extending Filters and KPIs 313 Deployment Best
Practices 317 Following Best Practices for PerformancePoint Data
Connections and Content Libraries 317 Deploying Dashboards Across Dev,
Test, and Production Environments 319 Customizing PerformancePoint
SharePoint Web Parts 321 Security and Configuration Best Practices 325
Configuring the Unattended Service Account in SharePoint 325 Optimizing
PerformancePoint Services Application Settings 326 Summary 328 Part IV
Deploying and Managing the Business Intelligence Solution 329 Chapter 15
Implementing a Self-Service Delivery Framework 331 Planning a Self-Service
Delivery Framework 331 Creating a Data Governance Plan for Enterprise,
Team, and Personal BI 332 Identifying Stakeholders, Subject Matter Experts,
and Data Stewards 334 Understanding Industry Compliance Considerations 334
Managing Data Quality and Master Data 337 Identifying Target Audience and
Roles 339 Developing a Training Plan 340 Inventorying Tools and Skillset
340 Understanding Data Quality Services 340 Understanding Master Data
Services 342 Managing Data Quality and Master Data in Excel 345 Business
Intelligence Features Across the Microsoft Data Platform Versions and
Editions 347 Defining Success Criteria 348 Summary 349 Chapter 16 Designing
and Implementing a Deployment Plan 351 What Is a Deployment Plan? 351 How
Do You Deploy Business Intelligence Code? 353 Using Analysis Services
(Multidimensional or Tabular) 354 Using Reporting Services 357 How Do You
Implement the Deployment Plan? 359 Planning the Deployment 359 Designing
Scripts 360 Documenting Steps 360 Testing the Plan 361 Training Your Staff
362 Summary 362 Chapter 17 Managing and Maintaining the Business
Intelligence Environment 363 Using SQL Server Reporting Services 363
Configuring Memory 365 Caching Data and Pre-Rendering Reports 368 Using
ExecutionLog Views 369 Working with SQL Server Analysis Services 372 Using
Multidimensional Models 372 Using Tabular Models 374 Using SharePoint to
Improve Performance 375 Summary 378 Chapter 18 Scaling the Business
Intelligence Environment 379 Why Would You Scale the Business Intelligence
Environment? 379 How Do You Scale Each Tool? 381 Using Analysis Services
(Multidimensional or Tabular) 381 Reporting Services 385 Using Power Pivot
and Power View 387 Summary 390 Index 391