In-depth Actionable Training from the Comfort of Your Own Desk

Prerequisite: None

Mark Peco

CBIP

Analytics Consultant and Instructor

Mark Peco, CBIP, is an experienced consultant, educator, and team builder. With graduate and undergraduate degrees in engineering from the University of Waterloo, he helps clients identify and build the necessary analytics capabilities that will drive business impact.

As a leading practitioner of business intelligence and analytics, Mark is a faculty member of TDWI and teaches companies on a global basis how to implement and govern “intelligent” business solutions. He is CBIP certified at the mastery level and maintains his professional focus at the intersection of business, operations, and technology. Mark has several years of energy industry experience based on a variety of roles in the pipeline, distribution, and production sectors.

Mark lives in the Toronto area and can be contacted via email.

Course Outline

Dimensional data is a core component of modern business intelligence and data warehouse implementations. Dimensionally organized data offers a more effective and adaptable solution to business analytics needs than can be achieved with relational data structures. Virtually anyone involved in business intelligence and data warehousing projects needs to have fundamental knowledge of the pathway from business questions to business analytics. This course traces that pathway.

The course begins with a comparison of relational and dimensional data organization and provides an example of business questions not readily answered using more traditional data structures of relational modeling. It then illustrates the steps to design analytics solutions, starting from business questions and concluding by demonstrating an OLAP solution. These steps encompass techniques to capture business questions, represent them as a business solution, translate them into a technology solution, and deliver them to those who need information.

You Will Learn

• Concepts of dimensional data modeling
• The relationship between business metrics and dimensional data
• Similarities and differences between relational and dimensional data models
• Requirements-gathering techniques for business metrics and dimensional data
• How to build a logical dimensional model
• How to translate a logical dimensional model to a star schema design
• How dimensional data is used to deliver business analytics and OLAP capabilities

Geared To

• Data architects
• Data mart developers
• Business analysts
• Business intelligence and data warehouse program and project managers