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How to learn data engineering

Christophe Blefari

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. Who are the data engineers?

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Python for Data Engineering

Ascend.io

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

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Charting A Path For Streaming Data To Fill Your Data Lake With Hudi

Data Engineering Podcast

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

Data Lake 130
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Cloud Native Data Orchestration For Machine Learning And Data Engineering With Flyte

Data Engineering Podcast

Summary Machine learning has become a meaningful target for data applications, bringing with it an increase in the complexity of orchestrating the entire data flow. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform.

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Data News — Week 24.08

Christophe Blefari

My ideas these days ( credits ) Hey, fresh Data News edition. This week I've participated to a round table about data and did a cool presentation about Engines. The idea was to depict the history of engines over the last 40 years and what leads to polars and DuckDB. Is it Java/Scala or Python?

Data Lake 130
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Insights And Advice On Building A Data Lake Platform From Someone Who Learned The Hard Way

Data Engineering Podcast

Summary Designing a data platform is a complex and iterative undertaking which requires accounting for many conflicting needs. Designing a platform that relies on a data lake as its central architectural tenet adds additional layers of difficulty. Missing data? Struggling with broken pipelines? Stale dashboards?

Data Lake 100
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Add Version Control To Your Data Lake With LakeFS

Data Engineering Podcast

Summary Data lakes are gaining popularity due to their flexibility and reduced cost of storage. Along with the benefits there are some additional complexities to consider, including how to safely integrate new data sources or test out changes to existing pipelines.

Data Lake 100