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Introduction to Apache Kafka: Fundamentals and Working

Analytics Vidhya

All these sites use some event streaming tool to monitor user activities. […]. The post Introduction to Apache Kafka: Fundamentals and Working appeared first on Analytics Vidhya.

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Streaming Machine Learning Without a Data Lake

ODSC - Open Data Science

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

Hadoop Distributed File System (HDFS) : HDFS is a distributed file system designed to store vast amounts of data across multiple nodes in a Hadoop cluster. Distributed File Systems : Distributed Systems often rely on distributed file systems to manage data storage across nodes and ensure efficient data access and retrieval.

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Apache Flink for all: Making Flink consumable across all areas of your business

IBM Journey to AI blog

Event-driven businesses across all industries thrive on real-time data, enabling companies to act on events as they happen rather than after the fact. This is where Apache Flink shines, offering a powerful solution to harness the full potential of an event-driven business model through efficient computing and processing capabilities.

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Building a Pizza Delivery Service with a Real-Time Analytics Stack

ODSC - Open Data Science

To understand what it means, we should start by thinking of the world in terms of events, where an event is a thing that happens. And we are going to take those events, become aware of them, and understand them. Stores events in a durable manner so that downstream components can process them.

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Among these tools, Apache Hadoop, Apache Spark, and Apache Kafka stand out for their unique capabilities and widespread usage. Apache Hadoop Hadoop is a powerful framework that enables distributed storage and processing of large data sets across clusters of computers.

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The Backbone of Data Engineering: 5 Key Architectural Patterns Explained

Mlearning.ai

In data engineering, the Pub/Sub pattern can be used for various use cases such as real-time data processing, event-driven architectures, and data synchronization across multiple systems. The company can use the Pub/Sub pattern to process customer events such as product views, add to cart, and checkout.