Why Move to Databricks? Start with Governance
For government agencies, a Databricks migration creates value when Unity Catalog is designed as the governance foundation, not added after workloads move.
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Practical analysis for consequential systems.
Articles on data modernization, AI architecture, governance, and the tradeoffs that determine whether a system can be trusted in practice.
Latest Analysis
What We Examine
The decisions underneath the technology.
The strongest architecture is not defined by a product list. It is defined by the choices an organization can explain, operate, and defend after implementation.
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Data platforms
Migration strategy, platform boundaries, interoperability, performance, cost, and the operational realities behind modernization.
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Governance and evidence
Ownership, access control, lineage, audit records, and the evidence required to reconstruct what happened later.
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AI systems
Retrieval, evaluation, controlled model use, human decisions, and the architecture needed to move from experiments to reliable systems.
Editorial Standard
Capability is only the beginning.
Each analysis moves beyond what a technology can do and examines what changes when an organization has to implement, govern, and operate it.
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Start with the real decision
Define the operational problem before recommending a platform, pattern, or migration.
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Make the tradeoffs visible
Show the cost, constraints, dependencies, and organizational work behind the technical benefit.
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Follow the evidence
Ask who owns the decision, what the system can prove, and where traceability stops.
Working through an architecture decision?
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