Ed-Fi 143

The Dimensional Data Warehouse

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This course will introduce you to the Kimball dimensional data warehouse and its importance when organizing data for analytical purposes. 

This course does not aim to be an exhaustive explanation of the topic, but rather its goal is to teach you why a dimensional data warehouse is important and introduce you to the concepts necessary before you proceed to the following course where you implement one. At the end of this course, we will recommend two books for you to read that will go further in depth. 

Ed-Fi 143 is a part of the larger Analytics Engineering Pathway and assumes you have already worked your way through the previous courses in the pathway. While you may continue without completing those, we recommend you pause here and start at the beginning of the pathway. Thus far on the pathway you have: 

  • Learned about the data engineering lifecycle 
  • Deployed a production-ready Ed-Fi Platform on Google Cloud 
  • Synced data from your student information system (SIS) to your Ed-Fi Platform 

Learning Objectives

The learning objectives for this course are: 

  • Understand the purpose of dimensional modeling and how it translated to a star schema 
  • Be able to imagine how your data could be modeled in the way described 

Course Outcome 

By the end of this course, Academy students will be able to: 

  • Understand the role of the Ed-Fi Platform in an analytics data stack 
  • Understand the need for a separate cloud data warehouse 
  • Understand the importance of dimensional modeling when creating datasets for use in analytics 

Who Should Enroll 

  • Students who are enrolled in the Analytics Engineering Pathway 
  • College students or non-K12 data people who desire to develop K12-specific engineering expertise 

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