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Course 20463: Implementing a Data Warehouse with Microsoft SQL Server 2014

Duration: 90-days online access
ILT Classroom: 5 days
Audience: IT Professionals
Certification: MCSA
Exam: 70-463
Level: 300

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Overview

About this course
This course describes how to implement a data warehouse platform to support a BI solution. Students will learn how to create a data warehouse with Microsoft® SQL Server® 2014, implement ETL with SQL Server Integration Services, and validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services..

Audience profile
This course is intended for database professionals who need to create and support a data warehousing solution. Primary responsibilities include:

  • Implementing a data warehouse.
  • Developing SSIS packages for data extraction, transformation, and loading.
  • Enforcing data integrity by using Master Data Services.
  • Cleansing data by 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 Control Flow in an SSIS Package.
  • Debug and Troubleshoot SSIS packages.
  • Implement an ETL solution that supports incremental data extraction.
  • Implement an ETL solution that supports incremental data loading.
  • 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 BI solutions can consume data from the data warehouse.

Pre-requisites
Before attending this course, students must 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.

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 you embark on a data warehousing project.
  • Module 2: Planning Data Warehouse Infrastructure
    This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
  • Module 3: Designing and Implementing a Data Warehouse
    This module describes the key considerations for the logical design of a data warehouse, and then discusses best practices for its physical implementation.
  • Module 4: Creating an ETL Solution with SSIS
    This module discusses considerations for implementing an ETL process, and then focuses on Microsoft SQL Server Integration Services (SSIS) as a platform for building ETL solutions.
  • Module 5: Implementing Control Flow in an SSIS Package
    This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
  • 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.
  • Module 7: Implementing a Data Extraction Solution
    This module describes the techniques you can use to implement an incremental data warehouse refresh process.
  • Module 8: Loading Data into a Data Warehouse
    This module describes the techniques you can use to implement data warehouse load process.
  • Module 9: Enforcing Data Quality
    This module introduces Microsoft SQL Server Data Quality Services (DQS), and describes how you can use it to cleanse and deduplicate data.
  • Module 10: Master Data Services
    Master Data Services provides a way for organizations to standardize data and improve the quality, consistency, and reliability of the data that guides key business decisions. This module introduces Master Data Services and explains the benefits of using it.
  • Module 11: Extending SQL Server Integration Services
    This module describes the techniques you can use to extend SSIS. The module is not designed to be a comprehensive guide to developing custom SSIS solutions, but to provide an awareness of the fundamental steps required to use custom components and scripts in an ETL process that is based on SSIS.
  • Module 12: Deploying and Configuring SSIS Packages
    In this module, students will learn how to deploy packages and their dependencies to a server, and how to manage and monitor the execution of deployed packages.
  • Module 13: Consuming Data in a Data Warehouse
    This module introduces business intelligence (BI) solutions and describes how you can use a data warehouse as the basis for enterprise and self-service BI.

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