8 posts
2026-03-17·1 min read
Seven-layer Lakehouse: Ingestion (Airbyte, Kafka), Processing (Spark, Flink, dbt), Storage Format (Iceberg, Delta), MinIO, Metadata, Trino, Consumption.
2026-03-17·2 min read
Strategic goals, project rationale, data ecosystem, Lakehouse scope, and success criteria for a unified data platform.
2026-03-17·2 min read
Seven-layer Lakehouse architecture: Ingestion, Processing, Storage Format, Storage, Metadata, Query, Consumption. Batch and streaming.
2026-03-17·2 min read
End-to-end data flow: sources (Core, CRM, Payment, Risk, API), Airbyte/Kafka/Flink, Spark/dbt, Iceberg/MinIO, DataHub, Trino, Superset/ML/API.
2026-03-17·2 min read
Ingestion Layer: collect from CRM, Core, Risk, Payment, API; batch (Airbyte) and streaming (Kafka); CDC, retry, schema registry, quality control.
2026-03-17·1 min read
Security & Privacy: protect all layers, RBAC, PII masking, audit, encryption, compliance with personal data protection regulations.
2026-03-17·2 min read
BRD appendix: 6 layers (Raw, Staging, Curated, Analytics, Lineage & Metadata, Audit); 4-step lineage raw→stg→cur→ana.
2026-03-17·1 min read
Intro to a 7-post series specifying each Lakehouse layer: Raw, Staging, Curated, Analytics, Metadata & Governance, Query & BI, Consumption.