By Pete Stiglich
Explores using big data platforms as a more flexible archive approach than tapes or traditional warehouses. Operational systems purge data to meet SLAs, but regulatory retention often requires storing records in their original format, which a warehouse (integrated and standardized) may not preserve. The post contrasts ‘archive’ versus ‘analytical integration’ and suggests that a big data stack can retain raw, source-shaped historical data at scale, potentially lowering cost and simplifying retrieval. It frames this as complementary to warehousing: big data can preserve original records while warehouses serve conformed, analytics-ready views.
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Pete Stiglich: Trusted Expert in Data Architecture & Modeling
Pete has over 30 years of data architecture, data management, and analytics experience, most of that time as a consultant in industries such as government, finance, healthcare, insurance, and more. He is an industry thought leader in data architecture and data modeling and has developed and taught many courses on these topics. Pete enjoys helping clients solve complex data problems, leveraging proven approaches such as “Modeling the business before modeling the solution” which provides a benefit to clients that many IT professionals miss.
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