Implementing a SQL 2016 Data Warehouse (SSIS)

★★★★★ 4.5/5

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 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.

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Course Information

Course Syllabus
Who It’s for
FAQs

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

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 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

After completing this module, you will be able to:

Describe the main hardware considerations for building a data warehouse
Explain how to use reference architectures and data warehouse appliances to create a data warehouse

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

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Lab : Implementing a Data Warehouse Schema

After completing this module, you will be able to:

Implement a logical design for a data warehouse
Implement a physical design for a data warehouse

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

After completing this module, you will be able to:

Create Columnstore indexes
Work with 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

After completing this module, you will be able to:

Describe the advantages of Azure SQL Data Warehouse
Implement an Azure SQL Data Warehouse
Describe the considerations for developing an Azure SQL Data Warehouse
Plan for migrating to 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

After completing this module, you will be able to:

Describe ETL with SSIS
Explore Source Data
Implement a Data Flow

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 Package

Lab : Using Transactions and Checkpoints

After completing this module, you will be able to:

Describe control flow
Create dynamic packages
Use containers

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

After completing this module, you will be able to:

Debug an SSIS package
Log SSIS package events
Handle errors in 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

After completing this module, you will be able to:

Describe incremental ETL
Extract modified data
Describe temporal tables

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 Data

Lab : De-duplicating Data

After completing this module, you will be able to:

Describe data quality services
Cleanse data using data quality services
Match data using data quality services
De-duplicate data using data quality services

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

After completing this module, you will be able to:

Describe the key concepts of master data services
Implement a master data service model
Manage master data
Create a master data hub

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

After completing this module, you will be able to:

Use custom components in SSIS
Use scripting in SSIS

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

After completing this module, you will be able to:

Describe an SSIS deployment
Deploy an SSIS package
Plan SSIS package execution

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

After completing this module, you will be able to:

Describe at a high level business intelligence
Show an understanding of reporting
Show an understanding of data analysis
Analyze data with Azure SQL data warehouse

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Audience Profile

The primary audience for this course are database professionals who need to fulfill 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.

Q: How is SSIS a data warehouse?

A: SSIS is designed for beginners and professionals with SQL Server Integration Service, a fast and easy data warehousing tool used for data extraction, transformation, and data loading. It makes it easy to load the data from one database to another database, such as SQL Server, Oracle, or Excel file, etc.

Q: Who is the target audience for the Implementing a SQL 2016 Data Warehouse (SSIS) course?

A: The target audience for the Implementing a SQL 2016 Data Warehouse (SSIS) course is database professionals, data warehousing professionals, BI developers, BI solutions professionals, software and ETdevdevelopers, and those with basic knowledge of SQL, seeking a career in business intelligence.

Q: How will this course help you achieve your goal?

A: This course will help you to achieve goals in certain ways, like understanding components of a data warehousing solution; implementing a logical and physical design to create a data warehouse; and most importantly, executing a physical design for a data warehouse.

Q: Does SQL Server work with a data warehouse?

A: Yes, SQL Server works with a data warehouse, but be careful of runaway costs. It can also be tough to tune your data warehouse performance and summarize the whole data from different database types in SQL Server.

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Testimonials?

Mohammed Aljbreen Operation Specialist, SAMA

The Clarity of the Content was very good. The explanation of the trainer with in-depth knowledge in a proper flow really impressed me to give 5 star rating.

Arindam Chakraborty Systems Specialist, King Abdullah University of Sciences & Technology

The Instructor was really impressive. Clear cut explanation of every topic he covered with real time scenarios.

Sher Afzal Khan Cloud Engineer, Cloud 9 Networks

The Trainer and the Course Material, both are good. Good flow of explanation with simple examples. The complete training was focused on current industry challenges.

Jawed Ahmad Siddiqui Sr. System Administrator, Saudi Ceramics

The Trainer’s presentation was impressed me to continue the course till end. Never feel bore till the entire sessions. She studied our mindset and follows.