SQL Server Training

Implementing a Data Warehouse with Microsoft SQL Server 2012

Microsoft 10777

Microsoft Certification

Length:	5 Days
Published:	February 08, 2012(In development)
Language(s):	English
Audience(s):	IT Professionals
Level:	200
Technology:	Microsoft SQL Server 2012
Type:	Course
Delivery Method:	Instructor-led (online)

About this Course

This 5-day instructor-led course 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 Beta version of this course (10777AB) utilizes pre-release software in the virtual machine for the labs. Microsoft SQL Server 2012 Release Candidate 0 (RC0) is used in this course. Some of the exercises in this course are SQL Azure enabled.

Audience Profile

The primary audience for this course are 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. Primary responsibilities will include:

Implementing as data warehouse
Developing SSIS packages for data extraction and loading/transfer/transformation
Enforcing data integrity using Master Data Services
Cleansing data using Data Quality Services

At Course Completion

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 Data Flow in an SSIS Package.
Debug and Troubleshoot SSIS packages.
Implement an SSIS solution that supports incremental DW 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 at source.
Extend SSIS with custom scripts and components.
Deploy and Configure SSIS packages.
Describe how information workers can consume data from the data warehouse.