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Implementing Data Models and Reports with Microsoft® SQL Server®

  • Course Code M20466
  • Duration 5 days

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Course Delivery

This course is available in the following formats:

  • Company Event

    Event at company

  • Public Classroom

    Traditional Classroom Learning

  • Virtual Learning

    Learning that is virtual

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Course Overview

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The focus of this five-day instructor-led course is on creating managed enterprise BI solutions. It describes how to implement multidimensional and tabular data models, deliver reports with Microsoft SQL Server Reporting Services, create dashboards with Microsoft SharePoint Server PerformancePoint Services, and discover business insights by using data mining.

Course Schedule

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Target Audience

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This course is intended for database professionals who need to fulfill a Business Intelligence Developer role to create analysis and reporting solutions.

Course Objectives

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  • Describe the components, architecture, and nature of a BI solution.
  • Create a multidimensional database with Analysis Services.
  • Implement dimensions in a cube.
  • Implement measures and measure groups in a cube.
  • Use MDX Syntax.
  • Customize a cube.
  • Implement a Tabular Data Model in SQL Server Analysis Services.
  • Use DAX to enhance a tabular model.
  • Create reports with Reporting Services.
  • Enhance reports with charts and parameters.
  • Manage report execution and delivery.
  • Implement a dashboard in SharePoint Server with PerformancePoint Services.
  • Use Data Mining for Predictive Analysis.

 

Course Content

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  • Module 1: Introduction to Business Intelligence and Data Modeling
  • Elements of an Enterprise BI Solution
  • The Microsoft Enterprise BI Platform
  • Planning an Enterprise BI Project
  • Lab : Exploring a BI Solution
  • Exploring the Data WarehouseExploring the Analysis Services Data Model
  • Exploring Reports
  • Module 2: Creating Multidimensional Databases
  • Introduction to Multidimensional Analysis
  • Creating Data Sources and Data Source Views
  • Creating a Cube
  • Overview of Cube Security
  • Lab : Creating a Multidimensional Database
  • Creating a Data Source
  • Creating and Modifying a Data Source View
  • Creating and Modifying a Cube
  • Adding a Dimension
  • Module 3: Working with Cubes and Dimensions
  • Configuring Dimensions
  • Defining Attribute Hierarchies
  • Sorting and Grouping Hierarchies
  • Lab : Defining Dimensions
  • Configuring Dimensions and Attributes
  • Creating Hierarchies
  • Creating a Hierarchy with Attribute Relationships
  • Creating a Ragged Hierarchy
  • Browsing Dimensions and Hierarchies in a Cube
  • Module 4: Working with Measures and Measure Groups
  • Working with Measures
  • Working with Measure Groups
  • Lab : Configuring Measures and Measure Groups
  • Configuring Measures
  • Defining a Regular Relationship
  • Configuring Measure Group Storage
  • Module 5: Introduction to MDX
  • MDX Fundamentals
  • Adding Calculations to a Cube
  • Using MDX to Query a Cube
  • Lab : Using MDX
  • Creating Calculated Members
  • Querying a Cube by Using MDX
  • Module 6: Enhancing a Cube
  • Working with Key Performance Indicators
  • Working with Actions
  • Working with Perspectives
  • Working with Translations
  • Lab : Customizing a Cube
  • Implementing an Action
  • Implementing Perspectives
  • Implementing a Translation
  • Module 7: Implementing an Analysis Services Tabular Data Model
  • Introduction to Analysis Services Tabular Data Models
  • Creating a Tabular Data Model
  • Using an Analysis Services Tabular Data Model in the Enterprise
  • Lab : Implementing an Analysis Services Tabular Data Model
  • Creating an Analysis Services Tabular Data Model Project
  • Configuring Columns and Relationships
  • Deploying an Analysis Services Tabular Data Model
  • Module 8: Introduction to DAX
  • DAX Fundamentals
  • Enhancing a Tabular Data Model with DAX
  • Lab : Using DAX to Enhance a Tabular Data Model
  • Creating Calculated Columns
  • Creating Measures
  • Creating a KPI
  • Implementing a Parent-Child Hierarchy
  • Module 9: Implementing Reports with SQL Server Reporting Services
  • Introduction to Reporting Services
  • Creating a Report with Report Designer
  • Grouping and Aggregating Data in a Report
  • Publishing and Viewing a Report
  • Lab : Creating a Report with Report Designer
  • Creating a Report
  • Grouping and Aggregating Data
  • Publishing a Report
  • Module 10: Enhancing Reports with SQL Server Reporting Services
  • Showing Data Graphically
  • Filtering Reports by Using Parameters
  • Lab : Enhancing a Report
  • Adding a Chart to a Report
  • Adding Parameters to a Report
  • Using Data Bars and Sparklines
  • Using a Map
  • Module 11: Managing Report Execution and Delivery
  • Managing Report Security
  • Managing Report Execution
  • Subscriptions and Data Alerts
  • Troubleshooting Reporting Services
  • Lab : Configuring Report Execution and Delivery
  • Configuring Report Execution
  • Implementing a Standard Subscription
  • Implementing a Data-Driven Subscription
  • Module 12: Delivering BI with SharePoint PerformancePoint Services
  • Introduction to SharePoint Server as a BI Platform
  • Introduction to PerformancePoint Services
  • PerformancePoint Data Sources and Time Intelligence
  • Reports, Scorecards, and Dashboards
  • Lab : Implementing a SharePoint Server BI Solution
  • Creating a SharePoint Server Site for BI
  • Configuring PerformancePoint Data Access
  • Creating PerformancePoint Reports
  • Creating a PerformancePoint Scorecard
  • Creating a PerformancePoint Dashboard
  • Module 13: Performing Predictive Analysis with Data Mining
  • Overview of Data Mining
  • Creating a Data Mining Solution
  • Validating a Data Mining Model
  • Consuming Data Mining Data
  • Lab : Using Data Mining to Support a Marketing Campaign
  • Using Table Analysis Tools
  • Creating a Data Mining Structure
  • Adding a Data Mining Model to a Data Mining Structure
  • Validating a Data Mining Model
  • Using a Data Mining Model in a Report

 

Course Prerequisites

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  • At least 2 years’ experience of working with relational databases, including:
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • Some basic knowledge of data warehouse schema topology (including star and snowflake schemas).
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.