87 articles tagged with "Data Engineering"

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.

Turn dashboards into decision tools: start with one business question, design for one audience, show the insight and next steps.

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

Cut scans from 2.3TB to 8GB and reduce compute costs 73% using Disk Cache, Spark cache, SQL result cache and improved file layout.

Use one Git branch model, short-lived branches with reviews and CI, map Dev/Stage/Prod, and keep notebooks and large files out of Git.

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

Practical Redis caching guide: design keys, set TTLs with jitter, choose eviction policies, monitor, scale, and secure production caches.

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.

Measuring the right ETL metrics—throughput, freshness, quality, cost, and scalability—prevents silent failures and runaway cloud spend.

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