Dimensional Data Modeling Primer: From Requirements to Business Analysis in Riyadh Jeddah Makkah Madinah Khobar Saudi Arabia KSA

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 analytic 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

Technical resources.

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