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Demystifying Modern Data Platforms

Cloudera

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

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Build Maintainable And Testable Data Applications With Dagster

Data Engineering Podcast

In this episode he explains his motivation for creating a product for data management, how the programming model simplifies the work of building testable and maintainable pipelines, and his vision for the future of data programming. Raghu Murthy, founder and CEO of Datacoral built data infrastructures at Yahoo!

Building 100
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Keeping Your Data Warehouse In Order With DataForm

Data Engineering Podcast

Dataform is a platform that helps you apply engineering principles to your data transformations and table definitions, including unit testing SQL scripts, defining repeatable pipelines, and adding metadata to your warehouse to improve your team’s communication. Visit Datacoral.com today to find out more.

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Data Scientist vs Data Engineer: Differences and Why You Need Both

AltexSoft

They set up resources required by the model, create pipelines to connect them with data, manage computer resources, and monitor and configure the model’s performance. Managing data and metadata. There are different ways how data can be stored: a data warehouse, numerous data lakes and data hubs , etc.

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Scaling Data Trust: How AutoTrader UK Migrated to a Decentralized Data Platform with Monte Carlo

Monte Carlo

“We want to empower Auto Trader and its customers to make data-informed decisions,” said Edward, “and democratize access to data through a self-serve platform.” Under this new model, decentralized alerts are routed to the appropriate team’s alerts channel.

Data 40