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Lakehouse Architecture

Summary​

Lakehouse architecture combines data lake flexibility with warehouse reliability. For enterprise AI, this enables one governed platform for ETL, analytics, model training, and retrieval use cases.

Why This Matters​

  • Reduces duplication between BI and AI pipelines.
  • Improves consistency of metrics used in decisions and prompts.
  • Enables lower-cost storage with governed performance tiers.

Core Concepts​

  • Open table formats for interoperability and schema evolution.
  • ACID guarantees for reliable incremental processing.
  • Separation of storage and compute for workload isolation.

Use the flow above to sequence decisions for Lakehouse Architecture before implementation starts.

Diagram​

Implementation Steps​

  1. Select open table format and define naming/versioning standards.
  2. Create zone policies for retention, masking, and ownership.
  3. Build incremental processing patterns for ingestion and curation.
  4. Define serving contracts for BI, ML, and retrieval workloads.
  5. Add cost and performance observability by workload class.

Realistic Example​

A financial services team moved fraud analytics and support-copilot embeddings to a shared lakehouse. They retired replicated marts and reduced data reconciliation incidents by 60 percent.

Senior Tech vs Dev Conversation​

Senior Tech: Why not keep separate platforms for analytics and AI? Dev: The same customer events get transformed twice and results conflict. Senior Tech: What is the key control? Dev: Zone-level governance with lineage and policy enforcement.

UX/UI Checklist​

  • Zone status and freshness are visible in the catalog.
  • Lineage graph is navigable from table to dashboard to model.
  • Consumers can see contract version and deprecation timeline.
  • Query performance and cost are shown per workload class.

Common Pitfalls​

  • Turning zones into folders without contract discipline.
  • Ignoring compaction strategy in streaming ingestion.
  • Migrating workloads before isolation is validated.

References and Next Steps​