28 articles tagged with "Data Governance"

Use LIME to explain single-model predictions: build local samples, fit a weighted surrogate, and verify stability, fidelity, and scope.

Layered lakehouse PII controls: column tags, catalog-driven masking/ABAC, lineage, audit logs, and automated deletion.

Map bounded contexts, classify relationships, and choose integration patterns to reduce rework, schema drift, and pipeline breakage.

Commands change state, events record facts, and projections build read models—covers aggregates, snapshots, concurrency, and replay.

Quickly compare ETL and ELT: when to transform data, plus trade-offs in cost, security, scalability, and use cases.

Matching AWS services to workload beats memorization—use access pattern, latency, and control to choose S3, Glue, Redshift, or Athena.

Standardize Gold tables, Unity Catalog metric views, and SQL Warehouses to deliver governed, consistent self-service analytics and BI access.

Choose a lakehouse for unified SQL, ML, and streaming - use open formats and governance to avoid lock-in and control costs.

Use Unity Catalog, system tables, SAT, and SIEM integrations to monitor lakehouse security, detect threats, and automate response.

Set Time Travel, Fail-safe, storage tiers and lifecycle policies to balance compliance, recovery, and storage cost in Snowflake.

Treat domain events as versioned API contracts—design for consumers, use outbox/CDC for reliable delivery, and enforce clear ownership.

AI and streaming data enable instant bid, budget, and audience adjustments to cut CPA, boost ROAS, and maintain governance.