Course 40009A:

Updating your Business Intelligence Skills to Microsoft SQL Server 2012

Length:3 Days
Published:June 29, 2012
Language(s):English
Audience(s):IT Professionals
Level:200
Technology:Microsoft SQL Server 2012
Type:Course
Delivery Method:Instructor-led (classroom)
About this Course
This three-day instructor-led course provides existing SQL Server Business Intelligence (BI) professionals with the knowledge and skills to use new and enhanced BI capabilities in SQL Server 2012.
Audience Profile
This course is intended for BI professionals with experience of using SQL Server 2008 R2.
At Course Completion
After completing this course, students will be able to:
  • Describe key new and enhanced features for BI in SQL Server 2012.
  • Use new and enhanced features in SQL Server Integration Services.
  • Manage data quality by using SQL Server Data Quality Services.
  • Manage master data by using new and enhanced features of SQL Server Master Data Services.
  • Use new and enhanced features of SQL Server Reporting Services.
  • Create tabular data models with PowerPivot and DAX.
  • Implement a tabular data model in SQL Server Analysis Services.
  • Use Power View to create interactive data visualizations.
  • Integrate Microsoft cloud technologies into a BI solution.
Course OutlineModule 1: Introduction to SQL Server 2012 for Business Intelligence
This module provides an overview of how SQL Server 2012 can be used to build BI solutions.
Lessons
  • Overview of SQL Server 2012 for Business Intelligence
  • SQL Server 2012 for Enterprise Integration Management
  • SQL Server 2012 for Data Warehousing
  • SQL Server 2012 for Data Analysis and Reporting
After completing this module, students will be able to:
  • Describe the role of SQL Server in a BI solution.
  • Describe features of SQL Server 2012 that support enterprise information management.
  • Describe features of SQL Server 2012 that support data warehousing.
  • Describe features of SQL Server 2012 that support data analysis and reporting.
Module 2: New and Enhanced Features in SQL Server Integration Services
This module describes the new and enhanced features in SQL Server Integration Services that can be used to create an ETL solution to load a data warehouse.
Lessons
  • Using the CDC Control Task for Incremental Data Loads
  • Deploying and Operating SSIS Packages
Lab : Using SQL Server Integration Services
  • Extracting Modified Data
  • Deploying and Operating an SSIS Project
After completing this module, students will be able to:
  • Use the CDC Control task to perform incremental data extractions in an ETL solution.
  • Deploy and operate an SSIS project.
Module 3: Data Quality Services
This module provides an introduction to SQL Server Data Quality Services, and teaches you how to build knowledge based data quality solutions for cleansing and matching data.
Lessons
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match Data
Lab : Cleansing Data
  • Creating a DQS Knowledge Base
  • Using a DQS Project to Cleanse Data
  • Using DQS in an SSIS Package
Lab : Deduplicating Data
  • Creating a Matching Policy
  • Using a DQS Project to Match Data
After completing this module, students will be able to:
  • Describe how Data Quality Services can help you manage data quality.
  • Use Data Quality Services to cleanse data.
  • Use Data Quality Services to match data.
Module 4: Master Data Services
This module provides an introduction to master data management with SQL Server 2012 Master Data Services.
Lessons
  • Introduction to Master Data Services
  • Implementing a Master Data Services Model
  • Managing Master Data
  • Creating a Master Data Hub
Lab : Implementing Master Data Services
  • Creating a Master Data Services Model
  • Using the Master Data Services Add-in for Excel
  • Enforcing Business Rules
  • Loading Data into a Model
  • Consuming Master Data Services Data
After completing this module, students will be able to:
  • Describe key Master Data Services concepts.
  • Implement a Master Data Services model.
  • Use Master Data Services tools to manage master data.
  • Use Master Data Services tools to create a master data hub.
Module 5: SQL Server 2012 Reporting Services
This module provides an introduction to new and enhanced features in SQL Server 2012 Reporting Services.
Lessons
  • Reporting Services Overview
  • Reporting Services and Microsoft SharePoint Server
  • Introduction to Data Alerts
Lab : Using SQL Server 2012 Reporting Services
  • Viewing SharePoint Mode Configuration
  • Authoring, Publishing, and Viewing a Report
  • Creating and Managing Data Alerts
After completing this module, students will be able to:
  • Describe the key capabilities of Reporting Services.
  • Install and configure Reporting Services in SharePoint Mode.
  • Use data alerts to notify users of changes to report data.
Module 6: Creating Tabular Data Models with PowerPivot
This module provides an introduction to new and enhanced features in PowerPivot.
Lessons
  • Introduction to Tabular Data Models and PowerPivot Technologies
  • Using PowerPivot
  • Using DAX in a PowerPivot Data Model
Lab : Using PowerPivot for Excel
  • Creating a Tabular Data Model by Using PowerPivot for Excel
  • Using a Tabular Data Model in Excel
  • Sharing a PowerPivot Workbook to PowerPivot Gallery
Lab : Creating Calculated Columns and Measures
  • Creating Calculated Columns
  • Creating Measures
After completing this module, students will be able to:
  • Describe the key features and benefits of tabular data models and PowerPivot technologies.
  • Create a PowerPivot for Excel workbook.
  • Share a PowerPivot for Excel workbook to PowerPivot Gallery and use a PowerPivot for Excel workbook as a data source.
Module 7: Implementing an Analysis Services Tabular Data Model
This module describes how to create tabular Analysis Services databases.
Lessons
  • Introduction to Analysis Services Tabular Data Model Projects
  • Developing an Analysis Services Tabular Data Model
Lab : Working with an Analysis Services Tabular Data Model
  • Creating an Analysis Services Tabular Data Model Project
  • Implementing a Perspective
  • Implementing Partitions
  • Deploying an Analysis Services Tabular Data Model
  • Using a Tabular Data Model
  • Configuring DirectQuery Storage Mode
  • Implementing Security in a Tabular Data Model
After completing this module, students will be able to:
  • Describe Analysis Services tabular data model projects.
  • Implement an Analysis Services tabular data model by Using SQL Server Data Tools.
Module 8: Creating Data Visualizations with Power View
This module provides an introduction to Power View, and describes how it can be used to create interactive data visualizations.
Lessons
  • Introduction to Power View
  • Visualizing Data with Power View
Lab : Creating Interactive Reports with Power View
  • Configuring a Tabular Data Model for Power View
  • Creating a Simple Power View Report
  • Using Interactive Visualizations
  • Creating a Scatter Chart and a Play Axis
  • Exporting a Power View Report to PowerPoint
After completing this module, students will be able to:
  • Describe the Power View and its place in the BI ecosystem.
  • Create data visualizations by using Power View.
Module 9: Using Cloud Technologies in a BI Solution
This module introduces Microsoft cloud technologies that can be used in a BI solution.
Lessons
  • Overview of Cloud Data Sources
  • SQL Azure
  • SQL Azure Reporting Services
  • The Windows Azure Marketplace DataMarket
Lab : Using Cloud Data in a BI Solution
  • Creating a SQL Azure Solution
  • Extracting Data from SQL Azure
  • Obtaining Data from the Windows Azure Marketplace DataMarket
After completing this module, students will be able to:
  • Describe cloud data scenarios.
  • Use SQL Azure.
  • Use SQL Azure Reporting Services.
  • Use the Windows Azure Marketplace DataMarket.
Before attending this course, students must have:
  • Experience of creating database solutions in SQL Server, including basic Transact-SQL programming.
  • Familiarity with data warehousing and BI solutions, including extract, transform, and load (ETL), data modeling, and reporting.
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