--- title: "#etl articles | Hashnode" description: "Extract, Transfer, Load. Read the latest #etl articles and tutorials on Hashnode." url: "https://hashnode.com/tag/etl" --- Tag # #etl 361 posts · 96 followers [Metrica Software](https://hashnode.com/@metrica) · [3d ago](https://hashnode.com/posts/data-virtualization-vs-etl-for-power-bi-when-live-access-beats-pipelines/6aed89de534f7b1f5a325ee8) ### [Data Virtualization vs ETL for Power BI: When Live Access Beats Pipelines](https://metrica.hashnode.dev/data-virtualization-vs-etl-for-power-bi-when-live-access-beats-pipelines?utm_source=hashnode&utm_medium=feed) Data virtualization for Power BI can shorten the delay between a source-system update and an operational decision. A report can query governed views without waiting for another warehouse load. That ad 12 min read · [metrica.hashnode.dev](https://metrica.hashnode.dev/data-virtualization-vs-etl-for-power-bi-when-live-access-beats-pipelines?utm_source=hashnode&utm_medium=feed) [ZyVOP](https://hashnode.com/@zyvop) · [Oct 21](https://hashnode.com/posts/kafka-connect-and-kafka-streams-moving-and-processing-data-96n2z/6ad86eafca7d264cbfa3d2b0) ### [Kafka Connect and Kafka Streams: Moving and Processing Data](https://blog.zyvop.com/kafka-connect-and-kafka-streams-moving-and-processing-data-96n2z?utm_source=hashnode&utm_medium=feed) Move data in and out of Kafka without writing custom code, then transform and aggregate it in flight with Kafka Streams. 9 min read · [blog.zyvop.com](https://blog.zyvop.com/kafka-connect-and-kafka-streams-moving-and-processing-data-96n2z?utm_source=hashnode&utm_medium=feed) [UpStep](https://hashnode.com/@upstep) · [Oct 10](https://hashnode.com/posts/does-this-etl-job-really-need-spark/6ac9d51fdfa98dbccdee760d) ### [Does This ETL Job Really Need Spark?](https://upstepasia.hashnode.dev/does-this-etl-job-really-need-spark?utm_source=hashnode&utm_medium=feed) Compare DuckDB and Spark for ETL. Learn workload trade-offs, AWS Glue considerations, and a practical project to test performance and correctness. 8 min read · [upstepasia.hashnode.dev](https://upstepasia.hashnode.dev/does-this-etl-job-really-need-spark?utm_source=hashnode&utm_medium=feed) [Dipak Mali](https://hashnode.com/@malidipak) · [Sep 26](https://hashnode.com/posts/slowly-changing-dimensions-scd-in-data-engineering/6ab830c84a9c6292b152a099) ### [Slowly Changing Dimensions (SCD) in Data Engineering](https://malidipak.hashnode.dev/slowly-changing-dimensions-scd-in-data-engineering?utm_source=hashnode&utm_medium=feed) While working with data warehouses, one common challenge is handling changes in dimension data while maintaining data accuracy and historical information. For example, consider a customer dimension: 8 min read · [malidipak.hashnode.dev](https://malidipak.hashnode.dev/slowly-changing-dimensions-scd-in-data-engineering?utm_source=hashnode&utm_medium=feed) [Metrica Software](https://hashnode.com/@metrica) · [Sep 18](https://hashnode.com/posts/why-enterprise-data-pipelines-break-and-the-hidden-cost-of-fixing-them/6aacf00a4b1a076cde1befb1) ### [Why Enterprise Data Pipelines Break and the Hidden Cost of Fixing Them](https://metrica.hashnode.dev/why-enterprise-data-pipelines-break-and-the-hidden-cost-of-fixing-them?utm_source=hashnode&utm_medium=feed) Enterprise data pipelines rarely fail as isolated jobs. They fail as chains of assumptions about schemas, schedules, credentials, capacity, and downstream consumers, so one upstream change can stop a 13 min read · [metrica.hashnode.dev](https://metrica.hashnode.dev/why-enterprise-data-pipelines-break-and-the-hidden-cost-of-fixing-them?utm_source=hashnode&utm_medium=feed) [Ciphemic academia](https://hashnode.com/@ciphemicacademia) · [Sep 16](https://hashnode.com/posts/data-engineer-career-path-beyond-the-clean-csv-import-2026/6aa9ebbf3f9ca93328e99e71) ### [Data Engineer Career Path: Beyond the Clean CSV Import (2026)](https://ciphemicacademia.hashnode.dev/data-engineer-career-path-beyond-the-clean-csv-import-2026?utm_source=hashnode&utm_medium=feed) Real data engineering is defined by messy data, scheduled pipelines, and systems that keep working when something breaks. Here's the real path. 7 min read · [ciphemicacademia.hashnode.dev](https://ciphemicacademia.hashnode.dev/data-engineer-career-path-beyond-the-clean-csv-import-2026?utm_source=hashnode&utm_medium=feed) [Mahesh RamSudama](https://hashnode.com/@maheshgupta) · [Aug 16](https://hashnode.com/posts/enterprise-data-migration-control-problem/6a812e3b25a265e3fe76fddb) ### [Four Enterprise Data Migrations Taught Me to Treat Migration as a Control Problem, Not a Copy Problem](https://thedebugledger.hashnode.dev/enterprise-data-migration-control-problem?utm_source=hashnode&utm_medium=feed) A practitioner’s framework for semantic mapping, reconciliation, cutover control, and business acceptance. 16 min read · [thedebugledger.hashnode.dev](https://thedebugledger.hashnode.dev/enterprise-data-migration-control-problem?utm_source=hashnode&utm_medium=feed) [areebakhizer7](https://hashnode.com/@areebakhizer) · [Aug 3](https://hashnode.com/posts/home-assistant-data-platform-prelude/6a7085b6b26ad397edfca448) ### [Unlocking Home Assistant Data: Building a Query Platform Part 1 — The Prelude](https://areebakhizer.hashnode.dev/home-assistant-data-platform-prelude?utm_source=hashnode&utm_medium=feed) HA deletes all history after 10 days. I built a pipeline to capture, store, and query it permanently. 4 min read · [areebakhizer.hashnode.dev](https://areebakhizer.hashnode.dev/home-assistant-data-platform-prelude?utm_source=hashnode&utm_medium=feed) [Scott McMahan](https://hashnode.com/@scottdudeman69) · [Aug 3](https://hashnode.com/posts/why-etl-developers-are-well-positioned-for-ai-engineering/6a70a4c6cb0808cd172f80dc) ### [Why ETL Developers Are Well Positioned for AI Engineering](https://aitransformeronline.hashnode.dev/why-etl-developers-are-well-positioned-for-ai-engineering?utm_source=hashnode&utm_medium=feed) See how ETL developers can use their pipeline and data-quality skills to transition into AI engineering, RAG, embeddings, and vector search. 3 min read · [aitransformeronline.hashnode.dev](https://aitransformeronline.hashnode.dev/why-etl-developers-are-well-positioned-for-ai-engineering?utm_source=hashnode&utm_medium=feed) [brooklyn](https://hashnode.com/@brkln) · [Jul 27](https://hashnode.com/posts/the-etl-pipeline-handbook-how-to-build-a-production-grade-pipeline-in-python/6a679921f4d9ad6845fede20) ### [The ETL Pipeline Handbook: How to Build a Production-Grade Pipeline in Python](https://freecodecamp.org/news/the-etl-pipeline-handbook-how-to-build-a-production-grade-pipeline-in-python?utm_source=hashnode&utm_medium=feed) Tracking flood risk takes one unglamorous but essential thing: clean and structured data. In this tutorial, you'll build a data pipeline yourself. You'll create a Python ETL (Extract, Transform, Load) 46 min read · [freecodecamp.org](https://freecodecamp.org/news/the-etl-pipeline-handbook-how-to-build-a-production-grade-pipeline-in-python?utm_source=hashnode&utm_medium=feed)