104 articles tagged with "Data Engineering"

Keys, windows, watermarks, triggers, and checkpoints for robust stateful stream aggregations in Spark and similar engines.

Serialize DAG runs with max_active_runs and throttle shared-resource tasks with pools, using both for correctness and capacity.

Branch, test, review, merge, and deploy dbt changes with focused commits, CI validation, protected branches, and rollback plans.

Build a reliable data stack by prioritizing batch pipelines, clear ownership, and a budget before adding streaming or AI.

How to build secure, branded embedded analytics with tenant isolation, scoped embeds, exports, and staged rollout.

Compare Flink, Kafka Streams, Spark, and Beam; test correctness, latency, recovery, and cost before choosing a streaming framework.

Measure P95/P99 before paying for provisioned concurrency — choose on‑demand or provisioned to balance tail latency, cost, and spikes.

Certifications can open screens, but salary follows role scope, production ownership, and measurable impact.

Explains how IoT Core ingests, filters, and routes device events, plus guidance on scaling, replay, and reliability.

Seven Databricks warehouse HA patterns to meet RTO/RPO: scaling, AZ resilience, failover, retries, stateless compute, standbys, isolation.

Design Airflow DAGs for safe retries and idempotent publishing: task boundaries, sensors, schedules, timeouts, and testing.

Use streaming events plus historical context to detect fraud across banking, e‑commerce, insurance, and telecom—making fast, accurate risk decisions.