Automated Load Patterns based on Source Data Profiles, AgileData Engineering Pattern #4 - Episode #70

Episode 70 of the Agile Data N’ Info podcast, hosted by AgileData, titled "Automated Load Patterns based on Source Data Profiles, AgileData Engineering Pattern #4 - Episode #70" was published on July 22, 2025 and runs 11 minutes.

July 22, 2025 ·11m · Agile Data N’ Info

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Summary

Join Shane Gibson and Nigel Vining as they describe and discuss the AgileData Engineering Pattern of Automated Load Patterns based on Source Data Profiles. The Automated Load Patterns based on Source Data Profiles pattern automatically profiles incoming data to determine its optimal loading method. It classifies data as either event data (immutable, append-only) or change data (evolving records) by analysing characteristics like unique key volume and column names over time. This automated classification then dictates the load strategy: an efficient partition replace for event data or a cost-effective upsert (end-dating historical records) for change data. This capability removes the manual burden and accelerates data onboarding, providing a trustworthy and efficient process even when the data type is initially unknown. 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/168912285/pattern-name Discover more AgileData Engineering Patterns over at https://agiledata.substack.com/s/agiledata-engineering-patterns If you just want to talk about making magic happen with agile and data you can connect with Shane @shagility on LinkedIn. Subscribe: Apple Podcast | Spotify | Google Podcast | Amazon Audible | TuneIn | iHeartRadio | PlayerFM | Listen Notes | Podchaser | Deezer | Podcast Addict | Buy the Green Book now! Simply Magical Data Ways of Working

Episode Description

Join Shane Gibson and Nigel Vining as they describe and discuss the AgileData Engineering Pattern of Automated Load Patterns based on Source Data Profiles.

The Automated Load Patterns based on Source Data Profiles pattern automatically profiles incoming data to determine its optimal loading method. It classifies data as either event data (immutable, append-only) or change data (evolving records) by analysing characteristics like unique key volume and column names over time. This automated classification then dictates the load strategy: an efficient partition replace for event data or a cost-effective upsert (end-dating historical records) for change data. This capability removes the manual burden and accelerates data onboarding, providing a trustworthy and efficient process even when the data type is initially unknown.

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/168912285/pattern-name

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

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