Remove kafka-streams-tables-part-3-event-processing-fundamentals
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5 Key Takeaways from Flink Forward 2023

Cloudera

Flink Forward is a great opportunity to learn about the cutting edge of streaming and stream processing technologies. This blog is a summary of what we observed there for anyone who was unable to attend or just wants to stay on top of what’s happening in streaming. billion events/s. Takeaway No.

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Addressing the Challenges of Sample Ratio Mismatch in A/B Testing

DoorDash Engineering

Experimentation isn’t just a cornerstone for innovation and sound decision-making; it’s often referred to as the gold standard for problem-solving, thanks in part to its roots in the scientific method. Figure 3: Reshuffling experiment after bug fix resolves SRM These are just two examples of how SRM can slip into experimentation.

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Deploying Kafka Streams and KSQL with Gradle – Part 1: Overview and Motivation

Confluent

The item picking process. Red Pill Analytics was hired to first design and th en implement all the necessary data integration processes required to connect Oracle WMS Cloud with their on-premises systems. This left us with only two data integration requirements to solve: relational tables and REST APIs. Inventory auditing.

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Journey to Event Driven – Part 3: The Affinity Between Events, Streams and Serverless

Confluent

FaaS functions only solve the compute part, but where is data stored and managed, and how is it accessed? What is more, as the world adopts the event-driven streaming architecture, how does it fit with serverless? The key to event-first systems design is understanding that a series of events captures behavior.

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The Evolution of Enforcing our Professional Community Policies at Scale

LinkedIn Engineering

In a previous blog post, we talked about how we built our anti-abuse platform using CASAL. In this blog post, we'll go deeper into how we manage account restrictions. When we detected that a member’s intent veered into abusive territory, we set the process of imposing restrictions in motion. data demanded an innovative solution.

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Journey to Event Driven – Part 2: Programming Models for the Event-Driven Architecture

Confluent

Part 1 of this series discussed why you need to embrace event-first thinking, while this article builds a rationale for different styles of event-driven architectures and compares and contrasts scaling, persistence and runtime models. Event-driven architecture. Event-driven, reactive architecture. Data evolution.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? Building streaming data pipelines for large data is enticing due to the velocity of the data. What is a Big Data Pipeline?