Implementing a SQL Data Warehouse

About this course

This 5 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.

Audience profile

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

Module 1: Introduction to Data Warehousing

Describe data warehouse concepts and architecture considerations.

Lessons

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

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

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

Module 8: Debugging and Troubleshooting SSIS Packages

This module describes how to debug and troubleshoot SSIS packages.

Lessons

  • 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

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

Lab : Extracting Modified DataLab : Loading Incremental Changes

Module 10: Enforcing Data Quality

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

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

Module 11: Using Master Data Services

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

Lessons

  • 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

  • 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

  • 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

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

Lab : Using Business Intelligence Tools

This course requires that you meet the following prerequisites:

  • Basic knowledge of the Microsoft Windows operating system and its core functionality
  • Working knowledge of relational databases
  • Some experience with database design

Auditoriniai mokymai

Pradžios data Trukmė, d. Kurso pavadinimas Kaina, € Statusas
2022-09-26 5 20761: Querying Data with Transact-SQL 1500 Užklausti
2022-10-03 5 20764: Administering a SQL Database Infrastructure 1500 Užklausti
2022-10-17 5 20767: Implementing a SQL Data Warehouse 1500 Užklausti
2022-09-26 4 10987: Performance Tuning and Optimizing SQL Databases 1400 Užklausti
2021-11-08 5 20762: Developing SQL Databases 1500 Užklausti
2022-11-07 5 20765: Provisioning SQL Databases 1500 Užklausti
2022-10-26 3 10988: Managing SQL Business Intelligence Operations 1200 Užklausti
2022-05-02 3 20768: Developing SQL Data Models 1200 Užklausti
2022-11-14 3 10989: Analyzing Data with Power BI 1200 Užklausti
2022-04-25 5 10990: Analyzing Data with SQL Server Reporting Services 1500 Užklausti

Nuotoliniai mokymai

Pradžios data Trukmė, d. Kurso pavadinimas Kaina, € Statusas
Užklausti 5 Administering a SQL Database Infrastructure (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Querying Data with Transact-SQL (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 3 Introduction to SQL Databases (nuotolinė klasė - ENG) 1200 Organizuojamas
Užklausti 5 Provisioning SQL Databases (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Querying Microsoft SQL Server (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Administering Microsoft SQL Server Databases (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 2 Querying SQL Databases Using T-SQL (nuotolinė klasė - ENG) 1100 Organizuojamas
Užklausti 2 Intermediate Querying SQL Databases Using T-SQL (nuotolinė klasė - ENG) 1100 Organizuojamas
Užklausti 5 Developing SQL Databases (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Implementing a SQL Data Models and Reports with Microsoft SQL Server (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Analyzing Data with SQL Server Reporting Services (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Implementing a SQL Data Warehouse (nuotolinė klasė - ENG) 1500 Organizuojamas
Užklausti 5 Microsoft Business Intelligence end to end with SQL Server 2016 (nuotolinė klasė - ENG) 1500 Organizuojamas