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Implementing a Data Warehouse with Microsoft SQL Server 2014 (20463)

COURSE TYPE

Intermediate

Course Number

8465

Duration

5 Days

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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.

This is a Microsoft Official Course (MOC) delivered by a Learning Tree expert instructor.

This course is part of a Microsoft Certification Path and can help you prepare for your MCSA Certification, MCSE Certification, or MCSD Certification.

Enhance your Microsoft skills and take your career to the next level with our Microsoft Training Success Pack.

You Will Learn How 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.

Important Course Information

Requirements:

  • 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.

Exam Information:

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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, students 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, students 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, students 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, students 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 Package

Lab : Using Transactions and Checkpoints

After completing this module, students 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, students 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 Data

Lab : Loading Incremental Changes

After completing this module, students 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 Data

Lab : De-duplicating data

After completing this module, students 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: Using 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.

Lessons

  • Master Data Services Concepts
  • Implementing a Master Data Services Model
  • Managing Master Data
  • Creating a Master Data Hub

Lab : Implementing Master Data Services

After completing this module, students will be able to:

  • Describe key Master Data Services concepts
  • Implement a Master Data Services model
  • Use Master Data Services tools to manage master data
  • Use Master Data Services tools to create a master data hub
  • Module 10: 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.

Lessons

  • Using Scripts in SSIS
  • Using Custom Components in SSIS

Lab : Using Custom Components and Scripts

After completing this module, students will be able to:

  • Include custom scripts in an SSIS package
  • Describe how custom components can be used to extend SSIS
  • Module 11: 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.

Lessons

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

Lab : Deploying and Configuring SSIS Packages

After completing this module, students will be able to:

  • Describe considerations for SSIS deployment.
  • Deploy SSIS projects.
  • Plan SSIS package execution.
  • Module 12: 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.

Lessons

  • Introduction to Business Intelligence
  • Introduction to Reporting
  • An Introduction to Data Analysis

Lab : Using Business Intelligence Tools

After completing this module, students will be able to:

  • Describe BI and common BI scenarios
  • Describe how a data warehouse can be used in enterprise BI scenarios
  • Describe how a data warehouse can be used in self-service BI scenarios
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Tuition — $1195

With a blend of video, text, hands-on labs, and knowledge checks, you will receive the same high quality content as the live event, but you can attend on your own time, at your own pace.

PLUS, we include access to a Microsoft Certified Trainer (MCT) to help you prepare for your certification exam and help you apply your new skills immediately… Learning Tree knows how to bring learning to life!

  • Flexibility to take the course on your own time, at your own pace
  • Forever access to the digital course materials – for any refreshers
  • You will receive a code with your purchase. The code may be redeemed for online access to this On Demand course for up to six months
  • Upon course activation, the MOC On Demand videos and labs are available for three months
  • 2 FREE hours of individual coaching from an MCT Learning Tree Instructor
  • This delivery is also eligible for Microsoft Assurance Training Vouchers (SATVs)

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Tuition

Standard

Government

In Classroom or
Online

Standard

$3710

Government

$3260

On Demand

$1195*

Private Team Training

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*prices exclude applicable taxes


Course Tuition Includes:

After-Course Instructor Coaching
When you return to work, you are entitled to schedule a free coaching session with your instructor for help and guidance as you apply your new skills.

After-Course Computing Sandbox
You'll be given remote access to a preconfigured virtual machine for you to redo your hands-on exercises, develop/test new code, and experiment with the same software used in your course.
Note: The Sandbox is not available for the On-Demand option.

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Training Hours

Standard Course Hours: 9:00 am – 4:30 pm
*Informal discussion with instructor about your projects or areas of special interest: 4:30 pm – 5:30 pm

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