Implementing a Data Warehouse with Microsoft SQL Server 2014 (M20463)

In this course, you will learn how to implement a data warehouse platform to support a business intelligence (BI) solution. You will discover how to create a data warehouse, implement extract, transform, and load (ETL) with SQL Server Integration Services (SSIS), and validate and cleanse data with SQL Server Data Quality Services (DQS) and SQL Server Master Data Services.

This course is designed for customers interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features of SQL Server 2014 as well as the important capabilities across the SQL Server data platform.

This course incorporates material from the Official Microsoft Learning Product 20463: Implementing a Data Warehouse with Microsoft SQL Server 2014. It covers the skills and knowledge measured by Exam 70-463 and along with on-the-job experience, helps you prepare for the exam.

    No classes are currenty scheduled for this course.

    Call (919) 283-1653 to get a class scheduled online or in your area!

1. Data Warehousing

  • Concepts and Architecture Considerations
  • Considerations for a Data Warehouse Solution

2. Data Warehouse Infrastructure

  • Hardware Selections
  • Data Warehouse Reference Architectures and Appliances

3. Design and Implement a Data Warehouse

  • Logical Design,
  • Physical Implementation

4. Create an ETL Solution with SSIS

  • ETL with SSIS
  • Explore Source Data
  • Implement Data Flow

5. Implement Control Flow in an SSIS Package

  • Control Flow
  • Create Dynamic Packages
  • Using Containers
  • Manage Consistency

6. Debug and Troubleshoot SSIS Packages

  • Debug an SSIS Package
  • Log SSIS Package Events
  • Handle Errors in an SSIS Package

7. Implement an Incremental ETL Process

  • Incremental ETL

8. Enforce Data Quality

  • Microsoft SQL Server DQS
  • Use DQS to Cleanse Data
  • Use DQS to Match Data

9. Master Data Services

  • Master Data Services Concepts
  • Implement a Master Data Services Model
  • Manage Master Data and Create a Master Data Hub

10. Extend SQL Server Integration Services (SSIS)

  • Custom Components in SSIS
  • Scripting in SSIS

11. Deploy and Configure SSIS Packages

  • Deployment Considerations
  • Deploy SSIS Projects
  • Plan SSIS Package Execution

12. Consume Data in a Data Warehouse

  • Business Intelligence Solutions
  • Reporting and Data Analysis

*Please Note: Course Outline is subject to change without notice. Exact course outline will be provided at time of registration.
  • Data warehouse concepts and architecture considerations
  • Select an appropriate hardware platform for a data warehouse
  • Design and implement a data warehouse
  • Implement data flow and control flow in a SSIS package
  • Debug and troubleshoot SSIS packages
  • Implement a SSIS solution that supports incremental data warehouse loads and extracting data
  • Implement data cleansing using Microsoft DQS
  • Implement Master Data Services (MDS) to enforce data integrity
  • Extend SSIS with custom scripts and components
  • Deploy and configure SSIS packages
  • How Business Intelligence solutions consume data in a data warehouse

Lab 1: Explore a Data Warehouse Solution

Lab 2: Data Warehouse Infrastructure Planning

Lab 3: Data Warehouse Implementation

Lab 4: Implement Data Flow in a SSIS Package

Lab 5A: Implement Control Flow in a SSIS Package

Lab 5B: Transactions and Checkpoints Usage

Lab 6: Debug and Troubleshoot a SSIS Package

Lab 7: Extract Modified Data

Lab 8: Data Warehouse Loading

Lab 9: Cleanse Data

Lab 10: Implement Master Data Services

Lab 11: Custom Scripts

Lab 12: Deploy and Configure SSIS Packages

Lab 13: Data Warehouse Usage in Enterprise and Self-Service BI Scenarios

  • Minimum two years experience working with relational databases, including designing a normalized database, creating tables and relationships
  • Basic programming constructs, including looping and branching
  • Focus on key business priorities, such as revenue, profitability, and financial account
  • Database professionals who need to fulfill a BI developer role focused on hands-on work, creating BI solutions included data warehouse implementation, ETL, and data cleansing
  • Database professionals responsible for implementing a data warehouse, developing SSIS packages for data extraction, loading, transferring, transforming, and enforcing data integrity using MDS, and cleansing data using DQS

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