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 Implementing a Data Warehouse with Microsoft SQL Server 2012 (MS 10777)

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5 Days
Implementing a Data Warehouse with Microsoft SQL Server 2012 (MS 10777)

 
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Course At A Glance

This course is one of three courses required to pass the MCSA: SQL Server exam.

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Implementing a Data Warehouse with Microsoft SQL Server 2012 (MS 10777)

Course Length: 5 Days

This course is one of three courses required to pass the MCSA: SQL Server exam.

Data warehousing is a solution organizations use to centralize business data for reporting and analysis. This five-day instructor-led course focuses on teaching individuals 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 exam 70-463.


Course Objectives

After completing this course, students will be able to:

  • Describe data warehouse concepts and architecture considerations.
  • Select an appropriate hardware platform for a data warehouse.
  • Design and implement a data warehouse.
  • Implement Data Flow in an SSIS Package.
  • Implement Control Flow in an SSIS Package.
  • Debug and Troubleshoot SSIS packages.
  • Implement an SSIS solution that supports incremental data warehouse loads and changing data.
  • Integrate cloud data into a data warehouse ecosystem infrastructure.
  • Implement data cleansing by using Microsoft Data Quality Services.
  • Implement Master Data Services to enforce data integrity.
  • Extend SSIS with custom scripts and components.
  • Deploy and Configure SSIS packages.
  • Describe how information workers can consume data from the data warehouse.

Pre-requisites

  • At least 2 years’ experience of working with relational databases, including:
  • Designing a normalized database.
  • Creating tables and relationships.
  • Querying with Transact-SQL.
  • 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.

Implementing a Data Warehouse with Microsoft SQL Server 2012 (MS 10777)

Module 1: Introduction to Data Warehousing

    Lessons
  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
    Lab: Exploring a Data Warehousing Solution
  • Exploring data sources
  • Exploring an ETL solution
  • Exploring a data warehouse

Module 2: Data Warehouse Hardware

    Lessons
  • Considerations for Building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances

Module 3: Designing and Implementing a Data Warehouse

    Lessons
  • Logical Design for a Data Warehouse
  • Physical Design for a Data Warehouse
    Lab: Implementing a Data Warehouse Schema
  • Implementing a Star Schema
  • Implementing a Snowflake Schema
  • Implementing a Time Dimension Table

Module 4: Creating an ETL Solution with SSIS

    Lessons
  • Introduction to ETL with SSIS
  • Exploring Source Data
  • Implementing Data Flow
    Lab: Implementing Data Flow in a SSIS Package
  • Exploring Source Data
  • Transferring Data by Using a Data Flow Task
  • Using Transformations in a Data Flow

Module 5: Implementing Control Flow in an SSIS Package

    Lessons
  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing Consistency
    Lab: Implementing Control Flow in an SSIS Package
  • Using Tasks and Precedence in a Control Flow
  • Using Variables and Parameters
  • Using Containers
    Lab: Using Transactions and Checkpoints
  • Using Transactions
  • Using Checkpoints

Module 6: Debugging and Troubleshooting SSIS Packages

    Lessons
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
    Lab: Debugging and Troubleshooting an SSIS Package
  • Debugging an SSIS Package
  • Logging SSIS Package Execution
  • Implementing an Event Handler
  • Handling Errors in a Data Flow

Module 7: Implementing an Incremental ETL Process

    Lessons
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading Modified Data
    Lab: Extracting Modified Data
  • Using a DateTime Column to Incrementally Extract Data
  • Using a Change Data Capture
  • Using Change Tracking
    Lab: Loading Incremental Changes
  • Using a Lookup Transformation to Insert Dimension Data
  • Using a Lookup Transformation to Insert or Update Dimension Data
  • Implementing a Slowly Changing Dimension
  • Using a MERGE Statement to Load Fact Data

Module 8: Incorporating Data from the Cloud into a Data Warehouse

    Lessons
  • Overview of Cloud Data Sources
  • SQL Server Database
  • The Windows Azure Marketplace
    Lab: Using Cloud Data in a Data Warehouse Solution
  • Creating a SQL Azure Database
  • Extracting Data from a SQL Azure Database
  • Obtaining Data from the Windows Azure Marketplace

Module 9: Enforcing Data Quality

    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

Module 10: Using Master Data Services

    Lessons
  • Introduction to Master Data Services
  • Implementing a Master Data Services Model
  • Using the Master Data Services Add-in for Excel
    Lab: Implementing Master Data Services
  • Creating a Basic Model
  • Editing a Model by Using the Master Data Services Add-in for Excel
  • Loading Data into a Model
  • Enforcing Business Rules
  • Consuming Master Data Services Data

Module 11: Extending SQL Server Integration Services

    Lessons
  • Using Custom Components in SSIS
  • Using Scripts in SSIS
    Lab: Using Custom Components and Scripts
  • Using a Custom Component
  • Using a Script Task

Module 12: Deploying and Configuring SSIS Packages

    Lessons
  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution
    Lab: Deploying and Configuring SSIS Packages
  • Create a SSIS Catalog
  • Deploy an SSIS Project
  • Create Environments for an SSIS Solution
  • Running an SSIS Package in SQL Server Management Studio
  • Scheduling SSIS Packages with SQL Server Agent

Module 13: Consuming Data in a Data Warehouse

    Lessons
  • Introduction to Business Intelligence
  • Introduction to Reporting
  • Introduction to Data Analysis
    Lab: Using Business Intelligence Tools
  • Exploring a Reporting Services Report
  • Exploring a PowerPivot Workbook
  • Exploring a Power View Report

MCSA: SQL Server 2012

MCSA: SQL Server 2012

The skills for your professional career

Demonstrate your essential skills and breakthrough insights in developing and maintaining the next wave of mission-critical environments.

Earning an MCSA: SQL Server 2012 certification will qualify you for a position as a database developer or database analyst.

Step

Exam title

Optional training

Required exam

1

Querying Microsoft SQL Server 2012

10774
461

2

Administering Microsoft SQL Server 2012 Databases

10775462

3

Implementing a Data Warehouse with Microsoft SQL Server 2012

10777463

 

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