Dimensional Data Model
Basics
Jack G. Zheng
Spring 2022
http://idi.kennesaw.edu/it4713
http://idi.kennesaw.edu/it7123
https://www.edocr.com/v/bmvojelj/jgzheng/dimensional-model
IT 4713 BI System
IT 7123 BI
Overview
• Dimensional model basic concepts
• Dimensional model as relational schemas
– Star schema, snowflake schema
• Basic dimension modeling techniques and
process
2
Dimensional model is the basis of multidimensional
analysis. It is also the foundation of traditional BI - data
warehouse design and OLAP reporting. The concepts are
still used in many modern BI tools including Power BI. This
lecture notes introduce the basics the dimensional data
model and its design at the conceptual and logical level.
Data Model Review
• A data model conceptualizes data elements and standardizes how the data elements relate to
one another
• Why data model (in BI and analytics)?
– Facilitates the understanding, query, reporting, analysis, and other use of data
– Creating business meaning & context
– Understand source and target data systems
– Optimize data structures to align queries and reports
•
Three levels: conceptual vs. logical vs. physical data models.
•
Typical data models
– Entity relationship model (a conceptual model)
– Relational data model (a logical model)
– Dimensional data model
– Graph (network) data model
– Hierarchical data model
3
Image from
https://www.slideshare.net/Dataversity/ldm-webinar-
data-modeling-business-intelligence and also view the
webinar https://www.dataversity.net/ldm-webinar-
data-modeling-business-intelligence/
The complexity
increases from
conceptual to
logical to
physical.’;[[[[[[[g
For complete info, refer to the IT
3703 data model lecture notes.
Dimensional Data Model
• Dimensional data model is a data model that specifically constructed around the
elements of facts and dimensions
–
It is directly based on the most common business questions and queries
– The platform for (traditional) BI.
• Dimensional model is a conceptual model and can be implemented in a logical