Skip to main content
search
0
Scalefree Knowledge Webinars Data Vault Friday Pivotizing Fact Measures in Data Vault

Watch the Video

In our continuous Data Vault Friday series, our CEO Michael Olschimke engages with a pertinent question from our audience.

“There are 6 measure values (float/decimal values) in the fact entity. In each row, typically 3 of them are NULL. Would it make sense to unpivot the data and encode this in a dimension for measure type? We also have measure values which are based on integers. Does it make sense to separate them into their own fact entity?”

In this insightful video, Michael delves into the considerations surrounding the structure of fact entities when dealing with multiple-measure values. The specific scenario of having null values for some measures prompts a discussion on whether it is beneficial to unpivot the data and encode it in a dimension for measure type. Additionally, Michael explores the case of measuring values based on integers and evaluates whether separating them into their own fact entity is a sound approach.

The video offers practical guidance and best practices for optimizing the design of fact entities in Data Vault models, ensuring efficiency and clarity in data representation.

Meet the Speaker

Profile picture of Michael Olschimke

Michael Olschimke

Michael has more than 15 years of experience in Information Technology. During the last eight years he has specialized in Business Intelligence topics such as OLAP, Dimensional Modelling, and Data Mining. Challenge him with your questions!

The Data Vault Handbook

Build your path to a scalable and resilient Data Platform

The Data Vault Handbook is an accessible introduction to Data Vault. Designed for data practitioners, this guide provides a clear and cohesive overview of Data Vault principles.

Read the Book Now

Leave a Reply

Close Menu