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Apache Kafka use cases: Driving innovation across diverse industries

IBM Journey to AI blog

Apache Kafka is an open-source , distributed streaming platform that allows developers to build real-time, event-driven applications. With Apache Kafka, developers can build applications that continuously use streaming data records and deliver real-time experiences to users. How does Apache Kafka work?

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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

Unlike traditional batch processing, where data is processed in fixed intervals, stream processing enables organizations to gain insights and respond to events as they happen in real-time.

Big Data 195
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Introduction to Apache NiFi and Its Architecture

Pickl AI

Guaranteed Delivery : NiFi ensures that data delivered reliably, even in the event of failures. It maintains a write-ahead log to ensure that the state of FlowFiles preserved, even in the event of a failure. Provenance Repository : This repository records all provenance events related to FlowFiles. Is Apache NiFi Easy to Use?

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A Simple Guide to Real-Time Data Ingestion

Pickl AI

Real-Time Data Ingestion Examples Here are some examples of real-time data ingestion applications: Internet of Things (IoT) Devices: IoT devices generate a vast amount of data, such as temperature, humidity, location, and sensor readings. Real-time data enables immediate updates to players’ positions, scores, and game state.

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Training Models on Streaming Data [Practical Guide]

The MLOps Blog

Streaming data is a continuous flow of information and a foundation of event-driven architecture software model” – RedHat Enterprises around the world are becoming dependent on data more than ever. A streaming data pipeline is an enhanced version which is able to handle millions of events in real-time at scale.

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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

Diagnostic Analytics Projects: Diagnostic analytics seeks to determine the reasons behind specific events or patterns observed in the data. 3. Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. Root cause analysis is a typical diagnostic analytics task.