Course Information
Code20767
FeeSee particular events - prices exclude VAT
Duration4 Day(s)
Delivery MethodInstructor-led
Scheduled DatesCurrently there are no scheduled events for this course - please contact us for information
Referral Fee£50 Amazon Voucher! - refer a friend or colleague
Related LinksN/A
MS 20767 Implementing a SQL Data Warehouse SQL Course Sheffield London Manchester Leeds Yorkshire Book Your Course Now!

Rezound provide official 20767 Implementing a SQL Data Warehouse training for Sheffield, London, Leeds, Manchester, Yorkshire and at your site in the UK.

Course Details

Introduction

This 4-day instructor led 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® 2016 and with Azure SQL Data Warehouse, to implement ETL with SQL Server Integration Services, and to validate and cleanse data with SQL Server Data Quality Services and SQL Server Master Data Services.

Related Certifications and Examinations

There can be many combinations for how a course's content maps to the various examinations and related certifications.

We have listed as many of the primary ones as possible and continually update our database - please contact us for further information.

Related Examinations

Related Certifications

Audience

The primary audience for this course are 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.

At Course Completion

After completing this course, students will be able to:

  • Describe the key elements of a data warehousing solution
  • Describe the main hardware considerations for building a data warehouse
  • Implement a logical design for a data warehouse
  • Implement a physical design for a data warehouse
  • Create columnstore indexes
  • Implementing an Azure SQL Data Warehouse
  • Describe the key features of SSIS
  • Implement a data flow by using SSIS
  • Implement control flow by using tasks and precedence constraints
  • Create dynamic packages that include variables and parameters
  • Debug SSIS packages
  • Describe the considerations for implement an ETL solution
  • Implement Data Quality Services
  • Implement a Master Data Services model
  • Describe how you can use custom components to extend SSIS
  • Deploy SSIS projects
  • Describe BI and common BI scenarios

Prerequisites

Before attending this course, students should ideally 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

Materials

The student kit includes a comprehensive workbook and other necessary materials for this class.

Course Outline

Module 1: Introduction to Data Warehousing

Describe data warehouse concepts and architecture considerations.

Lessons and Activities

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

Lab : Exploring a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure

This module describes the main hardware considerations for building a data warehouse.

Lessons and Activities

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

Lab : Planning Data Warehouse Infrastructure

Module 3: Designing and Implementing a Data Warehouse

This module describes how you go about designing and implementing a schema for a data warehouse.

Lessons and Activities

  • Logical Design for a Data Warehouse
  • Physical Design for a Data Warehouse

Lab : Implementing a Data Warehouse Schema

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.

Lessons and Activities

  • Introduction to Columnstore Indexes
  • Creating Columnstore Indexes
  • Working with Columnstore Indexes

Lab : Using Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse

This module describes Azure SQL Data Warehouses and how to implement them.

Lessons and Activities

  • Advantages of Azure SQL Data Warehouse
  • Implementing an Azure SQL Data Warehouse
  • Developing an Azure SQL Data Warehouse
  • Migrating to an Azure SQ Data Warehouse

Lab : Implementing an Azure SQL Data Warehouse

Module 6: Creating an ETL Solution

At the end of this module you will be able to implement data flow in a SSIS package.

Lessons and Activities

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

Lab : Implementing Data Flow in an SSIS Package

Module 7: Implementing Control Flow in an SSIS Package

This module describes implementing control flow in an SSIS package.

Lessons and Activities

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

Lab : Implementing Control Flow in an SSIS Package

Lab : Using Transactions and Checkpoints

Module 8: Debugging and Troubleshooting SSIS Packages

This module describes how to debug and troubleshoot SSIS packages.

Lessons and Activities

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

Lab : Debugging and Troubleshooting an SSIS Package

Module 9: Implementing an Incremental ETL Process

This module describes how to implement an SSIS solution that supports incremental DW loads and changing data.

Lessons and Activities

  • Introduction to Incremental ETL
  • Extracting Modified Data
  • Temporal Tables

Lab : Extracting Modified Data

  • Lab : Loading Incremental Changes

Module 10: Enforcing Data Quality

This module describes how to implement data cleansing by using Microsoft Data Quality services.

Lessons and Activities

  • 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

Module 11: Using Master Data Services

This module describes how to implement master data services to enforce data integrity at source.

Lessons and Activities

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

Lab : Implementing Master Data Services

Module 12: Extending SQL Server Integration Services (SSIS)

This module describes how to extend SSIS with custom scripts and components.

Lessons and Activities

  • Using Custom Components in SSIS
  • Using Scripting in SSIS

Lab : Using Scripts and Custom Components

Module 13: Deploying and Configuring SSIS Packages

This module describes how to deploy and configure SSIS packages.

Lessons and Activities

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

Lab : Deploying and Configuring SSIS Packages

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.

Lessons and Activities

  • Introduction to Business Intelligence
  • Introduction to Reporting
  • An Introduction to Data Analysis
  • Analyzing Data with Azure SQL Data Warehouse

Lab : Using Business Intelligence Tools


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