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OD20463D: Implementing a Data Warehouse with Microsoft® SQL Server® 2014

$500.00 $350.00

Implementing a Data Warehouse with Microsoft® SQL Server® 2014

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.
Note: This course is designed for customers who are interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features in SQL Server 2014, but also the important capabilities across the SQL Server data platform.

Description

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.
Note: This course is designed for customers who are interested in learning SQL Server 2012 or SQL Server 2014. It covers the new features in SQL Server 2014, but also the important capabilities across the SQL Server data platform.

Audience profile

This course is intended for 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 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.

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.
Lessons

  • Overview of Data Warehousing
  • Considerations for a Data Warehouse Solution

Lab : Exploring a Data Warehousing Solution

After completing this module, you will be able to:

  • Describe the key elements of a data warehousing solution
  • Describe the key considerations for a data warehousing project


Module 2: Data Warehouse Hardware Considerations

This module discusses considerations for selecting hardware and distributing SQL Server facilities across servers.
Lessons

  • Considerations for building a Data Warehouse
  • Data Warehouse Reference Architectures and Appliances

Lab : Planning Data Warehouse Infrastructure

After completing this module, you will be able to:

  • Describe key considerations for BI infrastructure.
  • Plan data warehouse infrastructure.


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.
Lessons

  • Logical Design for a Data Warehouse
  • Physical design for a data warehouse

Lab : Implementing a Data Warehouse Schema

After completing this module, you will be able to:

  • Describe a process for designing a dimensional model for a data warehouse
  • Design dimension tables for a data warehouse
  • Design fact tables for a data warehouse
  • Design and implement effective physical data structures for a data warehouse

 

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.
Lessons

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

Lab : Implementing Data Flow in an SSIS Package

After completing this module, you will be able to:

  • Describe the key features of SSIS.
  • Explore source data for an ETL solution.
  • Implement a data flow by using SSIS


Module 5: Implementing Control Flow in an SSIS Package

This module describes how to implement ETL solutions that combine multiple tasks and workflow logic.
Lessons

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

Lab : Implementing Control Flow in an SSIS PackageLab : Using Transactions and Checkpoints

After completing this module, you will be able to:

  • Implement control flow with tasks and precedence constraints
  • Create dynamic packages that include variables and parameters
  • Use containers in a package control flow
  • Enforce consistency with transactions and checkpoints


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.
Lessons

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

Lab : Debugging and Troubleshooting an SSIS Package

After completing this module, you will be able to:

  • Debug an SSIS package
  • Implement logging for an SSIS package
  • Handle errors in an SSIS package


Module 7: Implementing an Incremental ETL Process

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

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

Lab : Extracting Modified DataLab : Loading Incremental Changes

After completing this module, you will be able to:

  • Plan data extraction
  • Extract modified data


Module 8: 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.
Lessons

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

Lab : Cleansing DataLab : De-duplicating data

After completing this module, you will be able to:

  • Describe how Data Quality Services can help you manage data quality
  • Use Data Quality Services to cleanse your data
  • Use Data Quality Services to match data


Module 9: Enforcing Data Quality

Ensuring the high quality of data is essential if the results of data analysis are to be trusted. SQL Server 2014 includes Data Quality Services (DQS) to provide a computer-assisted process for cleansing data values, as well as identifying and removing duplicate data entities. This process reduces the workload of the data steward to a minimum while maintaining human interaction to ensure accurate results.
Lessons

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

Lab : Cleansing DataLab : Deduplicating DataAfter completing this module, you will be able to:
• Describe how DQS can help you manage data quality.
• Use DQS to cleanse your data.
• Use DQS to match data.

Prerequisites

This course requires that you meet the following prerequisites:
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.

About Microsoft Official Course On-Demand

About Microsoft Official Course On-Demand

MOC On-Demand is an integrated combination of video, text, practical tasks and knowledge tests designed to help IT experts and developers to expand their knowledge about Microsoft technologies. The courses are a great alternative for anyone wanting to learn independently and at their own pace. They can also be used in the form of a Blended Class together with managed training courses, or as the basis for training solutions with mentoring and other learning programmes.

All Labs within a course can be accessed via the Microsoft Labs Online (MLO) platform. Participants enrolled on a course can start the Labs directly from within a course; they do not need to be set up separately.

Licence codes purchased for the new Skillpipe MOC On-Demand courses can now all be found in the “Digital Library” section. The licence codes for these courses are now provided via the Management Dashboard, just like for the dMOC courses.

System requirements for Skillpipe MOC On-Demand

Browser:

  • current version of Internet Explorer, Microsoft Edge, Google Chrome™ or Firefox®

Internet access:

  • broadband Internet connection (recommended: network bandwidth of over 4Mbps)

Screen resolution:

  • 1280 x 1024 or higher

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