Microsoft Course 10777 Training - MOC 6368 Class Outline

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• Jun 25 - Jun 29, 2013
• Sep 17 - Sep 21, 2013
• Dec 17 - Dec 21, 2013

• Hands-on instruction by a certified instructor
• Includes all course materials and practice exams
• Onsite Testing
• Breakfast and Lunch provided each day

Can't travel or you want to stay with your family or business. No problem! Stay in your own city and save the additional expenses of roundtrip airfare, lodging, transportation, and meals and receive the same great instruction live from our instructors in our Live Instructor-Led Remote Classroom Training.

Remote Classroom Training

Our Remote Classroom Training is a live class with students observing the instructor and listening through your computer speakers. You will see the instructor's computer, slides, notes, etc., just like in the classroom. You will be following along, doing work, labs, and individual assignments.

Exam 70-463 - This 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 students prepare for Exam 70-463.

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.

Course Outline

Module 1: Introduction to Data Warehousing

This module provides an introduction to the key components of a data warehousing solution and the high-level considerations you must take into account when embarking on a data warehousing project.

• Describe data warehouse concepts and architecture considerations
• Considerations for a Data Warehouse Solution

Describe data warehouse concepts and architecture considerations.

Module 2: Data Warehouse Hardware Considerations

This module describes the considerations for selecting the appropriate hardware platform for your data warehouse solution.

• The Challenges of Building a Data Warehouse
• Data Warehouse Reference Architectures
• Data Warehouse Appliances

Select an appropriate hardware platform for a data warehouse.

Module 3: Designing and Implementing a Data Warehouse

This module describes how to implement the logical and physical architecture of a data warehouse based on industry proven design principles.

• Logical Design for a Data Warehouse
• Physical Design for a Data Warehouse

Design and implement a schema for a data warehouse.

Module 4: Design and implement a schema for a data warehouse

This module discusses considerations for implementing an ETL process, and then focuses on SQL Server Integration Services (SSIS) as a platform for building ETL solutions.

• Introduction to ETL with SSIS
• Exploring Source Data
• Implementing Data Flow

Implement Data Flow in an SSIS Package

Module 5: Implementing Control Flow in an SSIS Package

This module describes how to implement control flow which allows users to design robust ETL processes for a data warehousing solution that coordinate data flow operations with other automated tasks.

• Introduction to Control Flow
• Creating Dynamic Packages
• Using Containers
• Managing Consistency

Implement control flow in an SSIS package.

Module 6: Debugging and Troubleshooting SSIS Packages

This module describes how you can debug packages to find the cause of errors that occur during execution. It then discusses the logging functionality built into SSIS that you can use to log events for troubleshooting purposes. Finally, the module describes common approaches for handling errors in control flow and data flow.

• Debugging an SSIS Package
• Logging SSIS Package Events
• Handling Errors in an SSIS Package

Debug and Troubleshoot SSIS packages.

Module 7: Implementing an Incremental ETL Process

This module describes the techniques you can use to implement an incremental data warehouse refresh process.

• Introduction to Incremental ETL
• Extracting Modified Data
• Loading Modified Data

Implement an SSIS solution that supports incremental DW loads and changing data.

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

This modules describes how integrate cloud data into a data warehouse ecosystem.

• Overview of Cloud Data Sources
• SQL Server Azure
• Azure Data Market

Integrate cloud data into a data warehouse ecosystem.

Module 9: Enforcing Data Quality

This modules describes how to use Data Quality Services (DQS) for cleansing and deduplicating your data.

• Introduction to Data Cleansing
• Using Data Quality Services to Cleanse Data
• Using Data Quality Services to Match Data

Implement data cleansing by using Microsoft Data Quality Services.

Module 10: Using Master Data Services

This module introduces Master Data Services and explains the benefits of using it in a business intelligence (BI) context. It also describes the key configuration options, explains how to import and export data and apply rules that help to preserve data integrity, and introduces the new Master Data Services Add-in for Excel.

• Master Data Services Concepts
• Implementing a Master Data Services Model
• Using the Master Data Services Excel Add-in

Implement Master Data Services to enforce data integrity at source.

Module 11: Extending SSIS

This module describes how to extend SSIS by using custom scripts and components.

• Using Custom Components in SSIS
• Using Scripting in SSIS

Extend SSIS with custom scripts and components

Module 12: Deploying and Configuring SSIS Packages

This modules describes how to deploy and configure SSIS packages.

• Overview of Deployment
• Deploying SSIS Projects
• Planning SSIS Package Execution

Deploy and configure SSIS packages.

Module 13: Consuming Data in a Data Warehouse

This module describes how information workers can consume data from the data warehouse.

• Using Excel to Analyze Data in a data Warehouse.
• An Introduction to PowerPivot
• An Introduction to Crescent

Describe how information workers can consume data from the data warehouse.

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