Engineering & Integration
From Chaos to Clarity: How to Clean up Your Data Model
Cleaning up a data model is a strategic investment in the reliability, performance, and trustworthiness of your data products, and it should be looked upon as much more than a technical exercise. By following best practices like trimming unused data, filtering dimensions, indexing keys, and optimizing high-cardinality fields, you can transform a sluggish, error-prone model into a streamlined engine for insight.
Jul 14, 2025