ICT 772 - Advanced Data Transformation

Course Description

This course will provide instruction on architecture decisions when approaching a BI system, how to choose your technology and approach, building systems for growth and scalability, and ETL best practices. Real examples will be presented and students will develop a set of tools to help assess and make decisions regarding the technical architecture of a BI solution.

Course Details

Data transformation is at the centre of Business Intelligence (BI) systems; when implemented well, it is the foundation atop which a BI program can be built. Success of Business Intelligence solutions is heavily dependent on business perception of the accuracy, availability, and reliability of data. In order to achieve this, the quality of the data transformation layer is paramount. Furthermore, the definition of this layer is frequently riddled with complexities and a lack of obvious solutions.

In this course, students will delve into the different components that differentiate a sound ETL process and a poor one. To help achieve this, a set of practical tools will be taught providing students with the ability to analyze performance and architectural issues.

The course is designed for developers, DBAs and business users who wish to understand data transformation technologies better. Many topics are touched on at a basic level so students are expected to emerge with enough knowledge to feel comfortable making decisions and conversing with experts in the field.

Course Level Learning Outcomes

By completion of this course, successful students will be able to:

• Create advanced dimensional models
• Evaluate and optimize ETL packages
• Tune SQL queries for optimized performance
• Assess and develop a plan for scaling your database
• Describe and evaluate the value of emerging technologies and data challenges

Topics of Instruction

• Identify the strengths of different BI architectures and technologies
• Determine architectural and technological choices using business-driven criteria
• Analyze BI systems' growth patterns and plan for scale
• Assess and solve basic performance problems
• Identify best practices and shortcomings in an ETL process
• Assess and decide on the critical functions to an ETL solution