Trust Rules to validate your data, AgileData Engineering Pattern #3 - Episode #69

Join Shane Gibson and Nigel Vining as they describe and discuss the AgileData Engineering Pattern of Trust Rules to validate data.

 

The Trust Rules pattern provides automated data validation to ensure all incoming data is fit for purpose and trustworthy. It bakes in essential checks such as unique business keys and business effective dates, which run automatically upon data load or table refresh. Users can also define custom validation rules for specific columns. Results are collected, persisted, and surfaced via applications or alerts, with the system optimising validation for cost and speed through smart partitioning and clustered columns.

 

An AgileData Engineering Pattern is a repeatable, proven approach for solving a common data engineering challenge in a simple, consistent, and scalable way, designed to reduce rework, speed up delivery, and embed quality by default.

 

If you want a copy of the pattern template head over to:

https://agiledata.substack.com/i/167964917/pattern-name

Discover more  AgileData Engineering Patterns over at https://agiledata.substack.com/s/agiledata-engineering-patterns

 

If you want to join us on the next podcast, get in touch over at https://agiledata.io/podcasts/#contact

 

Or if you just want to talk about making magic happen with agile and data you can connect with Shane @shagility on LinkedIn.

 

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