45 articles tagged with "Analytics Engineering"

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

Checklist of Spark exam essentials: DataFrames/SQL, joins, partitions, performance, streaming, and testing for hands-on prep.

Keep analytics PRs small: state the change and impact, list affected metrics/models, and attach tests/screenshots for fast, accurate reviews.

Explains the PrestoDB vs Trino split, rename, shared architecture, deployment differences, and interview-focused workload guidance.

SQL-first platforms favor low-touch monitoring and credit controls, while Spark-heavy stacks demand deeper job and streaming observability.

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.

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

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

Practical Snowflake tuning: right-size warehouses, improve micro-partitioning, optimize SQL and caching to cut query latency.