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The Grand Vision And Present Reality of DataOps

Data Engineering Podcast

In this episode Kevin Stumpf, CTO of Tecton, Maxime Beauchemin, CEO of Preset, and Lior Gavish, CTO of Monte Carlo, discuss the grand vision and present realities of DataOps. How does security factor into the design of robust DataOps systems? What are some of the things that DataOps isn’t (despite what marketers might say)?

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. These systems are built on open standards and offer immense analytical and transactional processing flexibility. Why are They Essential?

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How Systems Thinking Can Be Applied To Agile Transformations

Knowledge Hut

Applying systems thinking views a system as a set of interconnected and interdependent components defined by its limits and more than the sum of their parts (subsystems). When one component of a system is altered, the effects frequently spread across the entire system. are the main objectives of systems thinking.

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The Recommendation System at Lyft

Lyft Engineering

This blog post focuses on the scope and the goals of the recommendation system, and explores some of the most recent changes the Rider team has made to better serve Lyft’s riders. Introduction: Scope of the Recommendation System The recommendation system covers user experiences throughout the ride journey.

Systems 87
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Types of Information Systems: 6 Information System Types and Applications

Knowledge Hut

The information system is a very vast concept that encompasses several aspects like database management, the communication system, various devices, several connections, the internet, collection, organization, and storing data and other information-related applications that are typically used in a business forum.

Systems 52
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Scaling the Instagram Explore recommendations system

Engineering at Meta

Explore is one of the largest recommendation systems on Instagram. Using more advanced machine learning models, like Two Towers neural networks, we’ve been able to make the Explore recommendation system even more scalable and flexible. locally popular media), which further contributes to system scalability.

Systems 92
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Apache Kafka Deployments and Systems Reliability – Part 1

Cloudera

In our Kafka Summit 2021 presentation, we took a brief overview of many different configurations that have been observed to date. In Part 1, the discussion is related to: Serial and Parallel Systems Reliability as a concept, Kafka Clusters with and without Co-Located Apache Zookeeper, and Kafka Clusters deployed on VMs. .

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