Analytics Vidhya

MARCH 10, 2023

Introduction Apache Kafka is a framework for dealing with many real-time data streams in a way that is spread out. It was made on LinkedIn and shared with the public in 2011.

Apache Kafka 287

Apache Kafka Data Pipeline Analytics Analytics 287

Analytics Vidhya

APRIL 28, 2023

Introduction Apache Kafka is an open-source publish-subscribe messaging application initially developed by LinkedIn in early 2011. It is a famous Scala-coded data processing tool that offers low latency, extensive throughput, and a unified platform to handle the data in real-time.

Apache Kafka 259

Apache Kafka Analytics Analytics Hadoop 259

Analytics Vidhya

DECEMBER 30, 2022

The post Introduction to Apache Kafka: Fundamentals and Working appeared first on Analytics Vidhya. Introduction Have you ever wondered how Instagram recommends similar kinds of reels while you are scrolling through your feed or ad recommendations for similar products that you were browsing on Amazon?

Apache Kafka 272

Apache Kafka Data Science Analytics Analytics 272

ODSC - Open Data Science

MAY 31, 2023

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.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

Pickl AI

JULY 20, 2023

Real-time Data Stream Analysis: Use Python with libraries like Apache Kafka and Apache Spark to process and analyze real-time data streams from sources like Twitter, sensors, or website logs. Implement real-time analytics to monitor trends or anomalies in the data.

Analytics 40

Analytics Analytics Big Data Big Data 40

Data Science Dojo

JULY 24, 2023

Clusters : Clusters are groups of interconnected nodes that work together to process and store data. Clustering allows for improved performance and fault tolerance as tasks can be distributed across nodes. Each node is capable of processing and storing data independently.

Big Data 195

Big Data Big Data Data Engineering Data Engineer 195

Mlearning.ai

MAY 16, 2023

The events can be published to a message broker such as Apache Kafka or Google Cloud Pub/Sub. One popular example of the MapReduce pattern is Apache Hadoop, an open-source software framework used for distributed storage and processing of big data. Here’s a high-level overview of how the MapReduce pattern works: A.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52