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Data engineers vs. data scientists

O'Reilly Media - Data

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

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Enhancing customer care through deep machine learning at Travelers

CIO

Collectively, the scope spans about 1,600 data analytics professionals in the company and we work closely with our technology partnersâ??more that cover areas of software engineering, infrastructure, cybersecurity, and architecture, for instance. But we have to bring in the right talent. more than 3,000 of themâ??that

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You still don’t need a feature store

Xebia

Prevent repeated feature development work Software engineering best practice tells us Dont Repeat Yourself ( DRY ). This applies to feature engineering logic as well. Stateful features need to be updated in real-time fashion as new data arrives. We convert this logic to a batch pipelines when moving to production.

Training 130
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Netflix at AWS re:Invent 2019

Netflix Tech

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint. Wednesday?—?December

AWS 15
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Improving Stream Data Quality with Protobuf Schema Validation

Confluent

Our quickly expanding business also means our platform needs to keep ahead of the curve to accommodate the ever-growing volumes of data and increasing complexity of our systems. The Deliveroo Engineering organisation is in the process of decomposing a monolith application into a suite of microservices.

Data 81
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Incremental Processing using Netflix Maestro and Apache Iceberg

Netflix Tech

These challenges are currently addressed in suboptimal and less cost efficient ways by individual local teams to fulfill the needs, such as Lookback: This is a generic and simple approach that data engineers use to solve the data accuracy problem. Users configure the workflow to read the data in a window (e.g.

Windows 87
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Netflix at AWS re:Invent 2019

Netflix Tech

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint. Wednesday?—?December

AWS 40