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One of the reasons behind the rise in data lakes’ adoption is their ability to handle massive amounts of data coming from diverse data sources,
- Iddo Avneri
Prefect is a workflow orchestration tool empowering developers to build, observe, and react to data pipelines. It’s the easiest way to transform any Python function
- Amit Kesarwani
Dagster is a cloud-native data pipeline orchestration tool for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.
- Amit Kesarwani
A step by step guide to the lakeFS Cloud playground environment In this document, you will learn the quickest way to get started with lakeFS,
- Iddo Avneri
Introduction Schema validation ensures that the data stored in the lake conforms to a predefined schema, which specifies the structure, format, and constraints of the
- Iddo Avneri
Introduction If you want to migrate or clone repositories from a source lakeFS environment to a target lakeFS environment then follow this tutorial. Your source
- Amit Kesarwani
- Robin Moffatt
If you work with a smaller dataset or do one-off jobs, the way you manage backfills isn’t that crucial. But what if you face constantly
- Iddo Avneri
A step by step guide to running pipelines on Bronze, Silver and Gold layers with lakeFS Introduction The Medallion Architecture is a software design pattern
- Iddo Avneri
MLOps is mostly data engineering. As organizations ride past the hype cycle of MLOps, we realize there is significant overlap between MLOps and data engineering.
- Vino SD
- Robin Moffatt
Processing what you’d call the “latest” data may sound simple, but in reality, it’s complex and challenging. When you gather time-based data, you’ll quickly notice
- Adi Polak
