Implementing a Data Warehouse using Microsoft SQL Server Training in Singapore

In addition to their professional experience, students who attend this training should already have the following technical knowledge:

Essential:

• Basic knowledge of the Microsoft Windows operating system and its core functionality.
• Working knowledge of Transact-SQL. (equivalent knowledge to QATSQL and QATSQLPLUS)

Nice to have:

• Working knowledge of relational databases.
• Some experience with database design.

Virtual Classroom

For learners attending remotely via any virtual classroom, an additional screen is required for this course to work through remote desktop labs and view training information. A remote Desktop will be provided using GoToMyPC or LearnOnDemand.

The additional screen must have a minimum screen size of 19 inch and minimum resolution of 1280x1024, with the vertical resolution (1024) being the most critical.

If you have questions,contact our Virtual team.

After completing this course, students will be able to:

• Design a data warehouse
• Build a data warehouse
• Implement ETL control and data tasks
• Control transactions and maintain consistency
• Implement incremental updates
• Manage and run packages
• Debug packages

Module 1 : Data warehouse Overview

This module introduces the main terms used within data warehousing.

Lessons:

• What is a data warehouse?
• Components of a data warehouse
• Data warehouse project roles
• Using SQL Server as a data warehousing solution
• Lab diagram

Module 2: Designing and implementing a data warehouse

This module is aimed at designing and implementing the data warehouse. The first few lessons cover the design including fact tables and different variations of dimension table.

Lessons:

• Dimensional Model
• Dimensions and fact tables
• Star and snowflake schemas
• Slowly changing dimensions
• Partitioned tables
• Measures
• Time and junk dimensions
• Indexes and compression
• LAB A: Designing a data warehouse
• LAB B: Creating the data warehouse
• LAB C: Create a fact table
• LAB D: Create dimension tables

Module 3: Implementing a control flow in an SSIS package

This module looks at the tasks within the control flow of the SSIS package. The lessons will cover the tasks primarily aimed at the data warehouse.

Lessons:

• Introduction to SSIS
• Control flow
• Advanced control flow
• Containers
• Precedence
• Consistency
• LAB A: Create a basic control flow task
• LAB B: Using variable and parameters
• LAB C: Using a for each loop
• LAB D: Using transactions and checkpoints

Module 4: Implementing extract, transform and load with SSIS

This module covers the aspects of the SSIS package working with the data flow.

Lessons:

• Introduction to extract, transform and load (ETL)
• Data sources
• Destinations and transformations
• LAB A: Using the SQL Server import and export wizard
• LAB B: Profiling a source
• LAB C: Implement a data flow with transformations

Module 5: Debugging and troubleshooting SSIS packages.

This module covers the tools available to record events and handle errors.

Lessons:

• SSIS debugging
• SSIS event logging
• Error handling
• LAB A: Debugging an SSIS package
• LAB B: Configuring event logging
• LAB C: Implement error handling

Module 6: Implementing an incremental ETL process

This module covers the creation and running of a SSIS package for implementing the change data capture (CDC) tool.

Lessons:

• Introduction to incremental extract, transform and load
• Configuring incremental ETL
• Keeping historical data
• LAB A: Using CDC
• LAB B: Implementing slowly changing dimensions

Module 7: Deploying and configuring SSIS packages

This module covers the deployment and scheduling of SSIS packages. The packages can use environment variables.

Lessons:

• Package deployment options
• Running SSIS packages
• Validation and logging
• LAB A: Creating an SSIS catalog, environments and deploying a project
• LAB B: Running an SSIS package