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A Prequel to Data Mesh

Towards Data Science

My personal take on justifying the existence of Data Mesh A senior stakeholder at one my projects mentioned that they wanted to decentralise their data platform architecture and democratise data across the organisation. When I heard the words ‘decentralised data architecture’, I was left utterly confused at first!

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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day. Can you describe what is driving the adoption of real-time analytics?

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Implementing a Pharma Data Mesh using DataOps

DataKitchen

Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. We’ve covered the basic ideas behind data mesh and some of the difficulties that must be managed. Figure 1: Data requirements for phases of the drug product lifecycle.

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Top-Paying Data Engineer Jobs in Singapore [2023 Updated]

Knowledge Hut

Engineers work with Data Scientists to help make the most of the data they collect and have deep knowledge of distributed systems and computer science. In large organizations, data engineers concentrate on analytical databases, operate data warehouses that span multiple databases, and are responsible for developing table schemas.

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How to Use KSQL Stream Processing and Real-Time Databases to Analyze Streaming Data in Kafka

Rockset

With all of these stream processing and real-time data store options, though, also comes questions for when each should be used and what their pros and cons are. I hope by the end you find yourself better informed and less confused about the real-time analytics landscape and are ready to dive in to it for yourself.

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Modern Customer Data Platform Principles

Data Engineering Podcast

Summary Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. How has that changed the architectural approach to CDPs? Want to see Starburst in action?

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Data Engineering Weekly #107

Data Engineering Weekly

The author narrates how OS-C adopted Data Contract and federated data governance strategy to help fight against climate change. link] Sponsored: Why You Should Care About Dimensional Data Modeling It's easy to overlook all of the magic that happens inside the data warehouse.