Sun.Apr 28, 2024

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Why did Golang lose to Rust for Data Engineering?

Confessions of a Data Guy

A few years ago I wasn’t sure, who was going to win, Golang seemed to be popular, and still is for that matter. When I first wrote a little Golang (~2+ years ago) I was just trying to see what the hype was all about. The funny thing is, at the time, and today, it […] The post Why did Golang lose to Rust for Data Engineering? appeared first on Confessions of a Data Guy.

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Build Your Second Brain One Piece At A Time

Data Engineering Podcast

Summary Generative AI promises to accelerate the productivity of human collaborators. Currently the primary way of working with these tools is through a conversational prompt, which is often cumbersome and unwieldy. In order to simplify the integration of AI capabilities into developer workflows Tsavo Knott helped create Pieces, a powerful collection of tools that complements the tools that developers already use.

Building 147
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Terms You Should Know If You’re Planning To Use Change Data Capture

Seattle Data Guy

If you’ve worked in data long enough, then you’ve likely come across the term change data capture. Often called CDC, change data capture involves tracking and recording changes in a database as they happen, and then transmitting these changes to designated targets. This can be crucial because some pipelines, in particular batch pipelines, don’t capture… Read more The post Terms You Should Know If You’re Planning To Use Change Data Capture appeared first on Seattle D

Database 130
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If:Else Logic and Complexity – Hiding the Pea.

Confessions of a Data Guy

I was recently confronted with an interesting conundrum when writing a complex data pipeline. It was an interesting problem that arose from my quest to reduce complexity in part of the design, which found itself creeping into another part, re-enforcing the classic idea of whether you can really make the complexity pea go away, or […] The post If:Else Logic and Complexity – Hiding the Pea. appeared first on Confessions of a Data Guy.

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Apache Airflow® Best Practices for ETL and ELT Pipelines

Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.

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Data Engineering Weekly #169

Data Engineering Weekly

Intuit: The Data Mesh Strategy Behind Intuit’s Global Financial Technology Platform The Data Product Builder platform is becoming increasingly important in enterprise data engineering. It offers more targeted and customized data asset building than the general-purpose data stack. Intuit writes about the growing data mesh strategy and the strategic focus area for building data products.