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 275

Apache Kafka Data Science Analytics Analytics 275

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.

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Apache Kafka Analytics Analytics Hadoop 256

Data Science Dojo

JULY 24, 2023

They allow data processing tasks to be distributed across multiple machines, enabling parallel processing and scalability. It involves various technologies and techniques that enable efficient data processing and retrieval. Stay tuned for an insightful exploration into the world of Big Data Engineering with Distributed Systems!

Big Data 195

Big Data Big Data Data Engineering Data Engineer 195

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

AWS Machine Learning Blog

OCTOBER 9, 2024

With ML-powered anomaly detection, customers can find outliers in their data without the need for manual analysis, custom development, or ML domain expertise. Using Amazon Glue Data Quality for anomaly detection Data engineers and analysts can use AWS Glue Data Quality to measure and monitor their data.

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AWS ML ML Data Quality 98