- Published 11/9/2017
- 1st Edition
Prepare for Microsoft Exam 70-767–and help demonstrate your real-world mastery of skills for managing data warehouses. This exam is intended for Extract, Transform, Load (ETL) data warehouse developers who create business intelligence (BI) solutions. Their responsibilities include data cleansing as well as ETL and data warehouse implementation. The reader should have experience installing and implementing a Master Data Services (MDS) model, using MDS tools, and creating a Master Data Manager database and web application. The reader should understand how to design and implement ETL control flow elements and work with a SQL Service Integration Services package.
Focus on the expertise measured by these objectives:
• Design, and implement, and maintain a data warehouse
• Extract, transform, and load data
• Build data quality solutionsThis Microsoft Exam Ref:
• Organizes its coverage by exam objectives
• Features strategic, what-if scenarios to challenge you
• Assumes you have working knowledge of relational database technology and incremental database extraction, as well as experience with designing ETL control flows, using and debugging SSIS packages, accessing and importing or exporting data from multiple sources, and managing a SQL data warehouse.
Implementing a SQL Data Warehouse
About the Exam
Exam 70-767 focuses on skills and knowledge required for working with relational database technology.
About Microsoft Certification
Passing this exam earns you credit toward a Microsoft Certified Professional (MCP) or Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of data warehouse management
Passing this exam as well as Exam 70-768 (Developing SQL Data Models) earns you credit toward a Microsoft Certified Solutions Associate (MCSA) SQL 2016 Business Intelligence (BI) Development certification.
See full details at: microsoft.com/learning
Table of Contents
CHAPTER 1 Design and implement a data warehouse
CHAPTER 2 Extract, transform, and load data
CHAPTER 3 Build data quality solutions