MCSA SQL Server 2012 Exam Code 70-463 Course Outline

Microsoft Course 10777:

Exam 70-463

This instructor-led course describes how to implement a BI platform supports the analysis of information workers. Students will learn how to create a 2012, execute ETL and data warehousing with SQL Server SQL Server integration services, and verify and clean up data quality with SQL Server data services, and SQL Server master data services.

This course explains students preparing for the exam 70-463.

Audience Profile:

The primary audience for this course is that database professionals need to perform business intelligence developer role. They will need to focus on creating a BI solution, including the practice of implementation of data warehousing, ETL, and data cleansing. Key responsibilities will include:

• As the data warehousing implementation
• Data extraction and loading of the SSIS package in developing countries/transfer/conversion
• Enforce data integrity using master data services
• Cleaning data data quality service

At Course Completion:

Upon completion of this course, students will be able to:

• Describes data storage concepts and architecture considerations.
• Select the appropriate hardware platform for data warehousing.
• Design and implementation of data warehousing.
• Implementing data flow SSIS packages.
• Implementing data flow SSIS packages.
• Debug and troubleshoot SSIS packages.
• Implement an SSIS solution, supports incremental data warehouse loading and changing data.
• Cloud data integration with data warehouse ecosystem infrastructure.
• Implementation of data cleaning by using the Microsoft data quality services.
• The source for master data services to enforce data integrity.
• SSIS extensions and custom scripting and components.
• Deploy and configure an SSIS package.
• Describes how information workers to consume data in the data warehouse.

Course Outline:

 Introduction to Data Warehousing:

This module provides data warehousing solutions and high level taking into account critical components that must be considered when data warehousing projects in General.

• Describes data storage concepts and architecture considerations
• Considerations for data warehousing solutions
• Describes data storage concepts and architecture considerations

Data Warehouse Hardware Considerations:

This module describes, you can consider in choosing the right hardware platform for your data warehousing solution.

• Build data warehousing challenges
• Data warehouse reference architecture
• Data warehouse appliances
• Select the appropriate hardware platform for data warehousing.

Implementing Control Flow in an SSIS Package:

This module describes how to implement robust ETL process allows users to design and data warehousing solution, coordination and other automation of the data flow task operations control flow.

• Brief introduction of control flow
• Creating a dynamic package
• Use a container
• Consistency management
• Implement control flow SSIS packages.

Incorporating Data from the Cloud in a Data Warehouse:

This specific module details how to assimilate files into a files factory ecosystem.

This module describes how to integrate data into a data warehouse ecosystem.

• Cloud data sources overview
• SQL Azure Server
• Azure data market

Cloud data into a data warehouse ecosystem.

Using Master Data Services:

This module covers the primary data services, and explained in business intelligence (BI) uses it in the context of the benefits. It also describes the key configuration options, explains how to import and export data and application rules, instructions to maintain the integrity of the data and introduction of the new master data services add-in for Excel.

• The concept of master data services
• Implementing a master data services model
• Use master data services load Excel

The source for master data services to enforce data integrity.