Implementing a Data Warehouse with Microsoft SQL Server 2012
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Microsoft

Implementing a Data Warehouse with Microsoft SQL Server 2012

Aim

Data warehousing is a solution organizations use to centralize business data for reporting and analysis.

Description

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.

Compulsory Topics
1: Introduction to Data Warehousing
2: Data Warehouse Hardware
3: Designing and Implementing a Data Warehouse
4: Creating an ETL Solution with SSIS
5: Implementing Control Flow in an SSIS Package
6: Debugging and Troubleshooting SSIS Packages
7: Implementing an Incremental ETL Process
8: Incorporating Data from the Cloud into a Data Warehouse
9: Enforcing Data Quality
10: Using Master Data Services
11: Extending SQL Server Integration Services
12: Deploying and Configuring SSIS Packages
13: Consuming Data in a Data Warehouse
Intended For

This course is intended for database professionals who need to fulfill 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.

Requirements
Before attending this course, student should preferably have:
  • 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.
Duration

5 Days – Full Time
40 Hours – Part Time

Examination

Exam 70-463

Learning Outcome
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.
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