Implementing a Data Warehouse with Microsoft SQL Server®

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This course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2014, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services. Note: This course is designed for customers who are interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features in SQL Server 2014, but also the important capabilities across the SQL Server data platform.

 

TARGET AUDIENCE

This course is intended for database professionals who need to fulfil a Business Intelligence Developer role.  They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing.

COURSE OBJECTIVES

  • 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 ETL solution that supports incremental data extraction.
  • Implement an ETL solution that supports incremental data loading.
  • 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 BI solutions can consume data from the data warehouse.

COURSE CONTENT

  • Module 1: Introduction to Data Warehousing
  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution
  • Lab : Exploring a Data Warehousing Solution
  • Module 2: Data Warehouse Hardware Considerations
  • Considerations for building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances
  • Lab : Planning Data Warehouse Infrastructure
  • Module 3: Designing and Implementing a Data Warehouse
  • Logical Design for a Data Warehouse
  • Physical design for a data warehouse
  • Lab : Implementing a Data Warehouse Schema
  • Module 4: Creating an ETL Solution with SSIS
  • Introduction to ETL with SSIS
  • Exploring Data Sources
  • Implementing Data Flow
  • Lab : Implementing Data Flow in an SSIS Package
  • Module 5: Implementing Control Flow in an SSIS Package
  • Introduction to Control Flow
  • Creating Dynamic Packages
  • Using Containers
  • Managing Consistency
  • Lab : Implementing Control Flow in an SSIS Package
  • Lab : Using Transactions and Checkpoints
  • Module 6: Debugging and Troubleshooting SSIS Packages
  • Debugging an SSIS Package
  • Logging SSIS Package Events
  • Handling Errors in an SSIS Package
  • Lab : Debugging and Troubleshooting an SSIS Package
  • Module 7: Implementing an Incremental ETL Process
  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Loading Modified data
  • Lab : Extracting Modified DataLab : Loading Incremental Changes
  • Module 8: Enforcing Data Quality
  • Introduction to Data Quality
  • Using Data Quality Services to Cleanse Data
  • Using Data Quality Services to Match data
  • Lab : Cleansing DataLab : De-duplicating data
  • Module 9: Using Master Data Services
  • Master Data Services Concepts
  • Implementing a Master Data Services Model
  • Managing Master Data
  • Creating a Master Data Hub
  • Lab : Implementing Master Data Services
  • Module 10: Extending SQL Server Integration Services
  • Using Scripts in SSIS
  • Using Custom Components in SSIS
  • Lab : Using Custom Components and Scripts
  • Module 11: Deploying and Configuring SSIS Packages
  • Overview of SSIS Deployment
  • Deploying SSIS Projects
  • Planning SSIS Package Execution
  • Lab : Deploying and Configuring SSIS Packages
  • Module 12: Consuming Data in a Data Warehouse
  • Introduction to Business Intelligence
  • Introduction to Reporting
  • An Introduction to Data Analysis
  • Lab : Using Business Intelligence Tools

COURSE PREREQUISITES

This course requires that you meet the following prerequisites:

  • 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.

Price Includes International Curriculum Courseware And Very Active Real-Time Labs.

Implementing a Data Warehouse with Microsoft SQL Server Content / Exam(s)

Schedule for Implementing a Data Warehouse with Microsoft SQL Server
Course#Course ContentsExam#
20463DImplementing a Data Warehouse with Microsoft SQL Server70-463

2 Hours Daily 3 Times a Week

Total Duration 3 Months

  • Model: MCSA
  • Manufacturer: Microsoft

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