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Unpacking The Seven Principles Of Modern Data Pipelines

Data Engineering Podcast

Summary Data pipelines are the core of every data product, ML model, and business intelligence dashboard. The folks at Rivery distilled the seven principles of modern data pipelines that will help you stay out of trouble and be productive with your data. Closing Announcements Thank you for listening!

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Data Engineering Weekly #173

Data Engineering Weekly

link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. S3 is the state-of-the-art software system of our age. However, is that all enough?

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How Data Engineering Teams Power Machine Learning With Feature Platforms

Data Engineering Podcast

In this episode Razi Raziuddin shares how data engineering teams can support the machine learning workflow through the development and support of systems that empower data scientists and ML engineers to build and maintain their own features. What is feature engineering is and why/to whom it matters?

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Building Data Pipelines That Run From Source To Analysis And Activation With Hevo Data

Data Engineering Podcast

Building reliable data pipelines is a complex and costly undertaking with many layered requirements. In order to reduce the amount of time and effort required to build pipelines that power critical insights Manish Jethani co-founded Hevo Data. Data stacks are becoming more and more complex.

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Effective Pandas Patterns For Data Engineering

Data Engineering Podcast

Summary Pandas is a powerful tool for cleaning, transforming, manipulating, or enriching data, among many other potential uses. As a result it has become a standard tool for data engineers for a wide range of applications. The only thing worse than having bad data is not knowing that you have it.

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Making The Total Cost Of Ownership For External Data Manageable With Crux

Data Engineering Podcast

In this episode Crux CTO Mark Etherington discusses the different costs involved in managing external data, how to think about the total return on investment for your data, and how the Crux platform is architected to reduce the toil involved in managing third party data. Tired of deploying bad data?

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Moving Machine Learning Into The Data Pipeline at Cherre

Data Engineering Podcast

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.