Efnisyfirlit

• Title Page
• Copyright
• Contents
• Introduction
• Part I Overview of the Microsoft Business Intelligence Toolset
  • Chapter 1 Which Analysis and Reporting Tools Do You Need?
    • Selecting a SQL Server Database Engine
      • Building a Data Warehouse
      • Selecting an RDBMS
    • Selecting SQL Server Analysis Services
    • Working with SQL Server Reporting Services
      • Understanding Operational Reports
      • Understanding Ad Hoc Reporting
    • Working with SharePoint
    • Working with Performance Point
    • Using Excel for Business Intelligence
      • What Is Power Query?
      • What Is Power Pivot?
      • What Is Power View?
      • Power Map
    • Which Development Tools Do You Need?
      • Using SQL Server Data Tools
      • Using SQL Management Studio
      • Using Dashboard Designer
      • Using Report Builder
    • Summary
  • Chapter 2 Designing an Effective Business Intelligence Architecture
    • Identifying the Audience and Goal of the Business Intelligence Solution
      • Who’s the Audience?
      • What Is the Goal(s)?
    • What Are the Data Sources?
      • Using Internal Data Sources
      • Using External Data Sources
    • Using a Data Warehouse (or Not)
    • Implementing and Enforcing Data Governance
    • Planning an Analytical Model
    • Planning the Business Intelligence Delivery Solution
    • Considering Performance
    • Considering Availability
    • Summary
  • Chapter 3 Selecting the Data Architecture that Fits Your Organization
    • Why Is Data Architecture Selection Important?
      • Challenges
      • Benefits
    • How Do You Pick the Right Data Architecture?
      • Understanding Architecture Options
      • Understanding Research Selection Factors
      • Interviewing Key Stakeholders
      • Completing the Selection Form
      • Finalizing and Approving the Architecture
    • Summary
• Part II Business Intelligence for Analysis
  • Chapter 4 Searching and Combining Data with Power Query
    • Downloading and Installing Power Query
      • Importing Data
      • Importing from a Database
      • Importing from the Web
      • Importing from a File
    • Transforming Data
      • Combining Data from Multiple Sources
      • Splitting Data
      • Aggregating Data
    • Introducing M Programming
      • A Glance at the M Language
      • Adding and Removing Columns Using M
    • Summary
  • Chapter 5 Choosing the Right Business Intelligence Semantic Model
    • Understanding the Business Intelligence Semantic Model Architecture
    • Understanding the Data Access Layer
      • Using Power Pivot
      • Using the Multidimensional Model
      • Using the Tabular Model
    • Implementing Query Languages and the Business Logic Layer
      • Data Analytics Expressions (DAX)
      • Multidimensional Expressions (MDX)
      • Direct Query and ROLAP
      • Data Model Layer
    • Comparing the Different Types of Models
    • Which Model Fits Your Organization?
      • Departmental
      • Team
      • Organizational
    • Summary
  • Chapter 6 Discovering and Analyzing Data with Power Pivot
    • Understanding Hardware and Software Requirements
    • Enabling Power Pivot
    • Designing an Optimal Power Pivot Model
      • Importing Only What You Need
      • Understanding Why Data Types Matter
      • Working with Columns or DAX Calculated Measures
    • Optimizing the Power Pivot Model for Reporting
      • Understanding Power Pivot Model Basics
      • Adding All Necessary Relationships
      • Adding Calculated Columns and DAX Measures
      • Creating Hierarchies and Key Performance Indicators (KPIs)
      • Sorting Your Data to Meet End-User Needs
      • Implementing Role-Playing Dimensions
    • Summary
  • Chapter 7 Developing a Flexible and Scalable Tabular Model
    • Why Use a Tabular Model?
      • Understanding the Tabular Model
      • Using the Tabular Model
      • Comparing the Tabular and Multidimensional Models
      • Understanding the Tabular Development Process
    • How Do You Design the Model?
      • Importing Data
      • Designing Relationships
      • Calculated Columns and Measures
    • How Do You Enhance the Model?
      • Adding Hierarchies
      • Designing Perspectives
      • Adding Partitions
    • How Do You Tune the Model?
      • Optimizing Processing
      • Optimizing Querying
    • Summary
  • Chapter 8 Developing a Flexible and Scalable Multidimensional Model
    • Why Use a Multidimensional Model?
      • Understanding the Multidimensional Model
      • Understanding the Multidimensional Model Process
    • How Do You Design the Model?
      • Creating Data Sources and the Data Source View
      • Using the Cube Creation Wizard
      • Adjusting Measures
      • Completing Dimensions
    • How Do You Enhance the Model?
      • Adding Navigation with Hierarchies
      • Using the Business Intelligence Wizard for Calculations
      • Using Partitions and Aggregations
    • How Do You Tune the Model?
      • Resolving Processing Issues
      • Querying
    • Summary
  • Chapter 9 Discovering Knowledge with Data Mining
    • Understanding the Business Value of Data Mining
      • Understanding Data Mining Techniques
      • Common Business Use Cases
      • Driving Decisions, Strategies, and Processes Through Data Mining
    • Getting the Basics Right
      • Understanding the Data
      • Training and Test Datasets
      • Defining the Data Mining Structure
      • The Data Mining Model
    • Applying the Microsoft Data Mining Techniques with Best Practices
      • Using Microsoft Association Rules
      • Grouping Data with Microsoft Clustering
      • Building Mining Models with Microsoft Naïve Bayes
      • Using the Microsoft Decision Trees
      • Using Microsoft Neural Network and Microsoft Logistic Regression
      • Using Microsoft Linear Regression and Microsoft Regression Trees
      • Microsoft Sequence Clustering
      • Forecasting with Microsoft Time Series
    • Developing and Deploying a Scalable and Extensible Data Mining Solution
      • Choosing Between a Relational or a Cube Source for Your Data Mining Structure
      • Deploying Data Mining Models
      • Using DMX to Query Data Mining Models
    • Maintaining Data Mining Models
      • Fine-Tuning the Data Mining Structure
      • Keeping the Data Model Relevant
      • Continuous Learning Cycle
    • Integrating Data Mining with Your BI Solution
      • Integrating Data Mining in Your DW and ETL Processes
      • Integrating Data Mining with Reporting Services
      • Data Mining in Excel
    • Summary
• Part III Business Intelligence for Reporting
  • Chapter 10 Choosing the Right Business Intelligence Visualization Tool
    • Why Do You Need to Choose?
      • Identifying Users
      • Selecting Tools
    • What Are the Selection Criteria?
      • Business Capabilities
      • Technical Capabilities
    • How Do You Gather the Necessary Information?
    • What Are the Business Intelligence Visualization Options?
      • Using SQL Server Reporting Services
      • Using Power View
      • Using Power Map
    • How Do You Create and Complete the Evaluation Matrix?
    • How Do You Verify and Complete the Process?
      • Evaluation Matrix #1
      • Evaluation Matrix #2
    • Summary
  • Chapter 11 Designing Operational Reports with Reporting Services
    • What Are Operational Reports and Reporting Services?
      • Understanding Analytical versus Operational Reports
      • Using Reporting Services
    • What Are Development Best Practices?
      • Using Source and Version Control
      • Using Shared Data Sources and Datasets
      • Creating Templates
    • What Are Performance Best Practices?
      • Investigating Performance
      • Performance Tuning
    • What Are Functionality Best Practices?
      • Using Visualizations
      • Using Filters and Parameters
      • Providing Drilldown and Drillthrough
    • Summary
  • Chapter 12 Visualizing Your Data Interactively with Power View
    • Where Does Power View Fit with Your Reporting Solution?
    • Power View System Requirements
    • Creating Power View Data Source Connections
      • Creating Data Sources Inside Excel
      • Creating Data Sources Inside SharePoint
    • Creating Power View Reports
      • Using SharePoint to Create Power View Reports
      • Using Multiple Views in Power View
      • Creating Power View Visualizations
      • Creating Tables
      • Converting Visualizations
      • Creating Matrices
      • Creating Charts
      • Creating Multiples
      • Creating Cards
      • Creating Maps
      • Using Excel to Create Power View Reports
    • Filtering Data with Power View
      • Adding Filters
      • Using Advanced Filters
      • Adding Slicers
      • Invoking Cross-Filters
      • Adding Tiles
      • Adding Filters to a Report URL
    • Exporting Power View Reports
    • Summary
  • Chapter 13 Exploring Geographic and Temporal Data with Power Map
    • How Power Map Fits into Reporting Solutions
      • Understanding Power Map Features and Advantages
      • Comparing Power Map to Other SQL Server Geospatial Reporting Tools
      • Understanding Power Map Requirements
    • Optimizing Your Data Model for Power Map
      • Using Tours, Scenes, and Layers in Power Map
      • Defining Geography Fields in Your Data Model
      • Defining Date and Time Fields in Your Data Model
    • Working with Geospatial and Temporal Data
      • Visualizing Data Aggregation
      • Creating a Power Map Tour
      • Visualizing Data Over Time with Rich Animations
    • Deploying and Sharing Power Map Visualizations
      • Sharing Power Map Tours
      • Enhancing Power Map Deployment and Configurations in Office 365
    • Summary
  • Chapter 14 Monitoring Your Business with PerformancePoint Services
    • Where Does PerformancePoint Services Fit with Your Reporting Solution?
      • Understanding PPS Features
      • When Is PPS the Right Choice?
      • Implementing PPS Requirements for SharePoint
    • Extending PPS Dashboards
      • Adding PerformancePoint Time Intelligence
      • Using Interactivity Features
      • Adding Reporting Services Reports to PerformancePoint
      • Extending Filters and KPIs
    • Deployment Best Practices
      • Following Best Practices for PerformancePoint Data Connections and Content Libraries
      • Deploying Dashboards Across Dev, Test, and Production Environments
      • Customizing PerformancePoint SharePoint Web Parts
    • Security and Configuration Best Practices
      • Configuring the Unattended Service Account in SharePoint
      • Optimizing PerformancePoint Services Application Settings
    • Summary
• Part IV Deploying and Managing the Business Intelligence Solution
  • Chapter 15 Implementing a Self-Service Delivery Framework
    • Planning a Self-Service Delivery Framework
      • Creating a Data Governance Plan for Enterprise, Team, and Personal BI
      • Identifying Stakeholders, Subject Matter Experts, and Data Stewards
      • Understanding Industry Compliance Considerations
      • Managing Data Quality and Master Data
      • Identifying Target Audience and Roles
      • Developing a Training Plan
    • Inventorying Tools and Skillset
      • Understanding Data Quality Services
      • Understanding Master Data Services
      • Managing Data Quality and Master Data in Excel
      • Business Intelligence Features Across the Microsoft Data Platform Versions and Editions
    • Defining Success Criteria
    • Summary
  • Chapter 16 Designing and Implementing a Deployment Plan
    • What Is a Deployment Plan?
    • How Do You Deploy Business Intelligence Code?
      • Using Analysis Services (Multidimensional or Tabular)
      • Using Reporting Services
    • How Do You Implement the Deployment Plan?
      • Planning the Deployment
      • Designing Scripts
      • Documenting Steps
      • Testing the Plan
      • Training Your Staff
    • Summary
  • Chapter 17 Managing and Maintaining the Business Intelligence Environment
    • Using SQL Server Reporting Services
    • Configuring Memory
      • Caching Data and Pre-Rendering Reports
      • Using ExecutionLog Views
    • Working with SQL Server Analysis Services
      • Using Multidimensional Models
      • Using Tabular Models
    • Using SharePoint to Improve Performance
    • Summary
  • Chapter 18 Scaling the Business Intelligence Environment
    • Why Would You Scale the Business Intelligence Environment?
    • How Do You Scale Each Tool?
      • Using Analysis Services (Multidimensional or Tabular)
      • Reporting Services
      • Using Power Pivot and Power View
    • Summary
• Index
• EULA

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