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MOC 10777 - Implementing a Data Warehouse with Microsoft SQL Server 2012

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Course duration

  • 5 Days

Course Outline

This Data Warehouse with Microsoft SQL Server 2012 instructor-led training describes how to implement a BI platform to support information worker analytics. Students will learn how to create a data warehouse with SQL Server 2012, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services. This course helps people prepare for the exam 70-463.

The primary audience for this course are database professionals who need to fulfil a Business Intelligence Developer role.

  • Learn to describe data warehouse concepts and architecture considerations.
  • Learn to select an appropriate hardware platform for a data warehouse.
  • Learn to design and implement a data warehouse.
  • Learn to implement Data Flow in an SSIS Package.
  • Learn to implement Data Flow in an SSIS Package.
  • Learn to debug and Troubleshoot SSIS packages.
  • Learn to implement an SSIS solution that supports incremental DW loads and changing data.
  • Learn to integrate cloud data into a data warehouse ecosystem infrastructure.
  • Learn to implement data cleansing by using Microsoft Data Quality Services.
  • Learn to implement Master Data Services to enforce data integrity at source.
  • Learn to extend SSIS with custom scripts and components.
  • Learn to deploy and Configure SSIS packages.
  • Learn to describe how information workers can consume data from the data warehouse.
  • Writing Queries with Microsoft SQL Server Transact-SQL
  1. Introduction to Data Warehousing
    1. Describe data warehouse concepts and architecture considerations
    2. Considerations for a Data Warehouse Solution
    3. Lab: Exploring a Data Warehousing Solution
      1. Exploring Data Sources
      2. Exploring an ETL Process
      3. Exploring a Data Warehouse
      4. Describe data warehouse concepts and architecture considerations.
  2. Data Warehouse Hardware Considerations
    1. The Challenges of Building a Data Warehouse
    2. Data Warehouse Reference Architectures
    3. Data Warehouse Appliances
    4. Lab: No lab
      1. Select an appropriate hardware platform for a data warehouse.
  3. Designing and Implementing a Data Warehouse
    1. Logical Design for a Data Warehouse
    2. Physical Design for a Data Warehouse
    3. Lab: Implementing a Data Warehouse Schema
      1. Implementing a Star Schema
      2. Implementing a Snowflake Schema
      3. Implement a Time Dimension Table
      4. Design and implement a schema for a data warehouse.
  4. Design and implement a schema for a data warehouse
    1. Introduction to ETL with SSIS
    2. Exploring Source Data
    3. Implementing Data Flow
    4. Lab: Implementing Data Flow in an SSIS Package
      1. Exploring Source Data
      2. Transfer Data with a Data Flow Task
      3. Using Transformations in a Data Flow
      4. Implement Data Flow in an SSIS Package
  5. Implementing Control Flow in an SSIS Package
    1. Introduction to Control Flow
    2. Creating Dynamic Packages
    3. Using Containers
    4. Managing Consistency
    5. Lab: Implementing Control Flow in an SSIS Package
      1. Using Tasks and Precedence in a Control Flow
      2. Using Variables and Parameters
      3. Using Containers
    6. Lab: Using Transactions and Checkpoints
      1. Using Transactions
      2. Using Checkpoints
      3. Implement control flow in an SSIS package.
  6. Debugging and Troubleshooting SSIS Packages
    1. Debugging an SSIS Package
    2. Logging SSIS Package Events
    3. Handling Errors in an SSIS Package
    4. Lab: Debugging and Troubleshooting an SSIS Package
      1. Debugging an SSIS Package
      2. Logging SSIS Package Execution
      3. Implementing an Event Handler
      4. Handling Errors in a Data Flow
      5. Debug and Troubleshoot SSIS packages.
  7. Implementing an Incremental ETL Process
    1. Introduction to Incremental ETL
    2. Extracting Modified Data
    3. Loading Modified Data
    4. Lab: Extracting Modified Data
      1. Using a DateTime Column to Incrementally Extract Data
      2. Using a DateTime Column to Incrementally Extract Data
      3. Using Change Tracking
    5. Lab: Loading Incremental Changes
      1. Using a Lookup task to insert dimension data
      2. Using a Lookup task to insert or update dimension data
      3. Implementing a Slowly Changing Dimension
      4. Using a MERGE statement to load fact data
      5. Implement an SSIS solution that supports incremental DW loads and changing data.
  8. Incorporating Data from the Cloud in a Data Warehouse
    1. Overview of Cloud Data Sources
    2. SQL Server Azure
    3. Azure Data Market
    4. Lab: Using Cloud data in a Data Warehouse Solution
      1. Extracting data from SQL Azure
      2. Acquiring Data from the Azure Data Market
      3. Integrate cloud data into a data warehouse ecosystem.
  9. Enforcing Data Quality
    1. Introduction to Data Cleansing
    2. Using Data Quality Services to Cleanse Data
    3. Using Data Quality Services to Match Data
    4. Lab: Cleansing Data
      1. Creating a DQS Knowledge Base
      2. Using a DQS Project to Cleanse Data
      3. Use DQS in an SSIS Package
    5. Lab: De-Duplicating Data
      1. Creating a Matching Policy
      2. Using a DQS Project to Match Data
      3. Implement data cleansing by using Microsoft Data Quality Services.
  10. Using Master Data Services
    1. Master Data Services Concepts
    2. Implementing a Master Data Services Model
    3. Using the Master Data Services Excel Add-in
    4. Lab: Implementing Master Data Services
      1. Creating a Basic MDS Model
      2. Editing an MDS Model With Excel
      3. Loading Data into MDS
      4. Enforcing Business Rules
      5. Consuming Master Data Services Data
      6. Implement Master Data Services to enforce data integrity at source.
  11. Extending SSIS
    1. Using Custom Components in SSIS
    2. Using Scripting in SSIS
    3. Lab: Using Scripts and Custom Components
      1. Using a Custom Component
      2. Using the Script Task
      3. Extend SSIS with custom scripts and components
  12. Deploying and Configuring SSIS Packages
    1. Overview of Deployment
    2. Deploying SSIS Projects
    3. Planning SSIS Package Execution
    4. Lab: Deploying and Configuring SSIS Packages
      1. Create an SSIS Catalog
      2. Deploy an SSIS Project
      3. Create Environments for an SSIS Solution
      4. Running an SSIS Package in SQL Server Management Studio
      5. Scheduling SSIS Packages with SQL Server Agent
      6. Deploy and configure SSIS packages.
  13. Consuming Data in a Data Warehouse
    1. Using Excel to Analyze Data in a data Warehouse.
    2. An Introduction to PowerPivot
    3. An Introduction to Crescent
    4. Lab: Using a Data Warehouse
      1. Use PowerPivot to Query the Data Warehouse
      2. Visualizing Data by Using Crescent
      3. Describe how information workers can consume data from the data warehouse.

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