Implementing a Data Warehouse with SQL Server (70-767)

Requirements:

Experience of working with relational databases

Description

This course describes how to implement a data warehouse 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.

Target Audience:

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.

Prerequisites :

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.

Students will learn how to :

Module 1: Introduction to Data Warehousing

This module describes data warehouse concepts and architecture consideration.

Overview of Data Warehousing
Considerations for a Data Warehouse Solution

Module 2: Planning Data Warehouse Infrastructure

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

Considerations for data warehouse infrastructure.
Planning data warehouse hardware.
Planning data warehouse software:

Module 3: Designing and Implementing a Data Warehouse

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

Designing dimension tables
Designing fact tables
Physical Design for a Data Warehouse

Module 4: Columnstore Indexes

This module introduces Columnstore Indexes.

Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes

Module 5: Implementing an Azure SQL Data Warehouse

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

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
Copying data with the Azure data factory

Module 6: Creating an ETL Solution

This module you will be able to implement data flow in a SSIS package.

Introduction to ETL with SSIS
Exploring Source Data
Implementing Data Flow

Module 7: Implementing Control Flow in an SSIS Package

This module describes implementing control flow in an SSIS package.

Introduction to Control Flow
Creating Dynamic Packages
Using Containers
Managing consistency.

Module 8: Debugging and Troubleshooting SSIS Packages

This module describes how to debug and troubleshoot SSIS packages.

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

Module 9: Implementing a Data Extraction Solution

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

Introduction to Incremental ETL
Extracting Modified Data
Loading modified data
Temporal Tables

Module 10: Enforcing Data Quality

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

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

Module 11: Using Master Data Services

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

Introduction to Master Data Services
Implementing a Master Data Services Model
Hierarchies and collections
Creating a Master Data Hub

Module 12: Extending SQL Server Integration Services (SSIS)

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

Using scripting in SSIS
Using custom components in SSIS

Module 13: Deploying and Configuring SSIS Packages

This module describes how to deploy and configure SSIS packages.

Overview of SSIS Deployment
Deploying SSIS Projects
Planning SSIS Package Execution

Module 14: Consuming Data in a Data Warehouse

This module describes how to debug and troubleshoot SSIS packages.

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

Preparing Data Warehouse Development environment
(SQL SERVER 2016 + VISUAL STUDIO 2015)

Workbook:
Getting started with SQL Server

Getting started with Azure SQL Server

Module 1: Introduction to Data Warehousing

Presentation:
https://slideplayer.com/slide/13826470/
Workbook:
https://docs.google.com/document/d/1VmsvCtRlkPCSawxrK0qFGbjvfDKJp9kcA5Vj80p3ims/edit?usp=sharing

Module 2: Planning Data Warehouse Infrastructure

Presentation:
https://slideplayer.com/slide/13680520/

Article:
https://www.mssqltips.com/sqlservertip/5872/infrastructure-planning-for-a-sql-server-data-warehouse/

Workbook:
https://docs.google.com/document/d/1jCX-T6l64Vj4Fv9cxX2HS-2xx9oaCJBuAwTcRtHIkxI/edit?usp=sharing

Module 3: Designing and Implementing a Data Warehouse

Slides:
https://slideplayer.com/slide/8573846/
Workbook:
https://docs.google.com/document/d/1Q7g19bAFT1nyWtulz7Q-UxZlclp24pIOjv2YlqiVEE4/edit?usp=sharing

Module 4: Columnstore Indexes

Article:
1) Columnstore indexes: Overview
2) Columnstore indexes - Data Warehouse
3) SQL Server Columnstore Indexes Demo
This demo requires AdventureWorks2012 database.
Workbook:
https://docs.google.com/document/d/19ztmEE4sXTQWrvztaJh4MDAn94ffJiNbzevHQwE4kJw/edit?usp=sharing

Module 5: Implementing an Azure SQL Data Warehouse

Article:
1)Data warehousing in Microsoft Azure
2)Dedicated SQL pool (formerly SQL DW) in Azure Synapse Analytics
3)Create and query a dedicated SQL pool (formerly SQL DW) in Azure synapse Analytics using the Azure portal
4)Load the data into the data warehouse
Workbook:

Module 6: Creating an ETL Solution
Module 7: Implementing Control Flow in an SSIS Package
Module 8: Debugging and Troubleshooting SSIS Packages
Module 9: Implementing a Data Extraction Solution
Module 12: Extending SQL Server Integration Services (SSIS)

Article:

Lesson 1: Create a Project and Basic Package with SSIS
In this lesson, you create a simple ETL package that extracts data from a single flat file, transforms the data using lookup transformations and finally loads the result into a fact table destination.

Lesson 2: Adding Looping with SSIS
In this lesson, you expand the package you created in Lesson 1 to take advantage of new looping features to extract multiple flat files into a single data flow process.

Lesson 3: Add Logging with SSIS
In this lesson, you expand the package you created in Lesson 2 to take advantage of new logging features.

Lesson 4: Add Error Flow Redirection with SSIS
In this lesson, you expand the package you created in lesson 3 to take advantage of new error output configurations.

Lesson 5: Add SSIS Package Configurations for the Package Deployment Model
In this lesson, you expand the package you created in Lesson 4 to take advantage of new package configuration options.

Lesson 6: Using Parameters with the Project Deployment Model in SSIS
In this lesson, you expand the package you created in Lesson 5 to take advantage of using new parameters with the project deployment model.

Workbook:
Workbook

Module 13: Deploying and Configuring SSIS Packages

Article:

Lesson 1: Preparing to Create the Deployment Bundle
In this lesson, you will get ready to deploy an ETL solution by creating a new Integration Services project and adding the packages and other required files to the project.

Lesson 2: Create the Deployment Bundle in SSIS
In this lesson, you will build a deployment utility and verify that the deployment bundle includes the necessary files.

Lesson 3: Install SSIS Packages
In this lesson, you will copy the deployment bundle to the target computer, install the packages, and then run the packages.

Workbook:
-

Module 10: Enforcing Data Quality

Article:

Workbook:
Data Quality Services

Module 11: Using Master Data Services

Article:

Workbook:
Master Data Services