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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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Maintain Your Data Engineers' Sanity By Embracing Automation

Data Engineering Podcast

Summary Building and maintaining reliable data assets is the prime directive for data engineers. While it is easy to say, it is endlessly complex to implement, requiring data professionals to be experts in a wide range of disparate topics while designing and implementing complex topologies of information workflows.

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Joe Reis Flips The Script And Interviews Tobias Macey About The Data Engineering Podcast

Data Engineering Podcast

Summary Data engineering is a large and growing subject, with new technologies, specializations, and "best practices" emerging at an accelerating pace. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool.

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Data News — Week 24.08

Christophe Blefari

JVM vs. SQL data engineer — There's a big discussion in the community about what real data engineering is. Is it Java/Scala or Python? It's a sterile debate: both are useful and can serve different organisations with different service level for data users and stakeholders.

Data Lake 130
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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

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Clean Up Your Data Using Scalable Entity Resolution And Data Mastering With Zingg

Data Engineering Podcast

Summary Despite the best efforts of data engineers, data is as messy as the real world. Entity resolution and fuzzy matching are powerful utilities for cleaning up data from disconnected sources, but it has typically required custom development and training machine learning models. Who is the target audience for Zingg?

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Discover And De-Clutter Your Unstructured Data With Aparavi

Data Engineering Podcast

Summary Unstructured data takes many forms in an organization. From a data engineering perspective that often means things like JSON files, audio or video recordings, images, etc. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder.