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 mertkavi.com
Building common components in Data Lakehouse is a necessity ยท Mert Kavi
| | newsroom.aboutrobinhood.com
Fresher Data Lake on AWSS3 - Robinhood Newsroom
4.5 parsecs away

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| | Robinhood's mission is to democratize finance for all. Continuous data analysis and data driven decision making at different levels within
| | dennyglee.com
Why Structured Streaming and Delta Lake for Batch ETL? - Denny Lee
4.9 parsecs away

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| | A common approach to developing data pipelines is to use Structured Streaming (aka Spark Structured Streaming) with Delta Lake. This allows you to perform near-real data processing using the same APIs for batch processing. All of this is on top of Delta Lake to ensure the transactional consistency of your data. With Project Lightspeed, Structured [...]
| | lakefs.io
The State of Data Engineering 2022 - Git for Data - lakeFS
2.4 parsecs away

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| | An update on all the latest tools and trends in the data engineering space for 2022.
| | www.morling.dev
Single Message Transformations - The Swiss Army Knife of Kafka Connect - Gunnar Morling
28.3 parsecs away

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| Do you remember Angus "Mac" MacGyver? The always creative protagonist of the popular 80ies/90ies TV show, who could solve about any problem with nothing more than a Swiss Army knife, duct tape, shoe strings and a paper clip? The single message transformations (SMTs) of Kafka Connect are almost as versatile as MacGyver's Swiss Army knife: How to change the timezone or format of date/time message fields? How to change the topic a specific message gets sent to? How to filter out specific records? SMTs can b...