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Seamless SQL And Python Transformations For Data Engineers And Analysts With SQLMesh

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. __init__ covers the Python language, its community, and the innovative ways it is being used.

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Build A Data Lake For Your Security Logs With Scanner

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Data Lake 147
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Keep Your Data Lake Fresh With Real Time Streams Using Estuary

Data Engineering Podcast

In this episode David Yaffe and Johnny Graettinger share the story behind the business and technology and how you can start using it today to build a real-time data lake without all of the headache. What is the impact of continuous data flows on dags/orchestration of transforms? Closing Announcements Thank you for listening!

Data Lake 162
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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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Reflecting On The Past 6 Years Of Data Engineering

Data Engineering Podcast

In that time there have been a number of generational shifts in how data engineering is done. Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? __init__ covers the Python language, its community, and the innovative ways it is being used.