Apache Kafka, Data Science and Hadoop

Apache Kafka

Data Science

Hadoop

Introduction to Apache Kafka: Fundamentals and Working

Analytics Vidhya

DECEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. The post Introduction to Apache Kafka: Fundamentals and Working appeared first on Analytics Vidhya. All these sites use some event streaming tool to monitor user activities. […]. . […].

Apache Kafka

Apache Kafka Data Science Analytics Analytics

A Detailed Guide of Interview Questions on Apache Kafka

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

Apache Kafka Analytics Analytics Hadoop

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Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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Trending Sources

22 Widely Used Data Science and Machine Learning Tools in 2020

Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya. Here’s a list of over 20.

Data Science

Data Science Machine Learning Machine Learning Analytics

Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

MORE WEBINARS

Streaming Machine Learning Without a Data Lake

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

Data Lakes Machine Learning Machine Learning Apache Kafka

Best Data Engineering Tools Every Engineer Should Know

Pickl AI

MARCH 19, 2025

Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. How is Data Engineering Different from Data Science?

Data Engineering

Data Engineering Data Engineering Data Engineering Data Engineer

Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

JULY 24, 2023

Distributed File Systems : Distributed Systems often rely on distributed file systems to manage data storage across nodes and ensure efficient data access and retrieval. 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.

Big Data

Big Data Big Data Data Engineering Data Engineering

Predicting the Future of Data Science

Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

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

ODSC - Open Data Science

JUNE 1, 2023

We’re going to assume that the pizza service already captures orders in Apache Kafka and is also keeping a record of its customers and the products that they sell in MySQL. Apache Pinot is a real-time OLAP database built at LinkedIn to deliver scalable real-time analytics with low latency. He tweets at @markhneedham.

Analytics

Analytics Analytics Apache Kafka Data Science

Did Big Data Deliver Business Transformation & Improved CX?

Alation

AUGUST 4, 2022

“Cloud has not replaced big data but lowered the cost of entry,” says Gildersleeve. “Setting up Hadoop on-premises was a huge undertaking. Spark, Tensorflow, Apache Kafka, et cetera, are all out found in cloud databases,” points out Jones. A key challenge of legacy approaches involved data quality. .

Big Data

Big Data Big Data Apache Kafka Data Lakes

Discover the Most Important Fundamentals of Data Engineering

Pickl AI

NOVEMBER 4, 2024

Additionally, Data Engineers implement quality checks, monitor performance, and optimise systems to handle large volumes of data efficiently. Differences Between Data Engineering and Data Science While Data Engineering and Data Science are closely related, they focus on different aspects of data.

Data Engineering

Data Engineering Data Engineering Data Engineering Data Engineer

Big Data Syllabus: A Comprehensive Overview

Pickl AI

AUGUST 9, 2024

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

Big Data

Big Data Big Data Big Data Analytics Big Data Analytics

A Comprehensive Guide to the main components of Big Data

Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. It is known for its high fault tolerance and scalability.

Big Data

Big Data Big Data Data Lakes Apache Hadoop

How data engineers tame Big Data?

Dataconomy

FEBRUARY 23, 2023

Solutions for managing and processing large volumes of data Data engineers can use various solutions to manage and process large volumes of data. This approach allows for faster and more efficient processing of large volumes of data.

Big Data

Big Data Big Data Data Engineering Data Engineering

Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. Implement real-time analytics to monitor trends or anomalies in the data.

Analytics

Analytics Analytics Big Data Big Data

Build Data Pipelines: Comprehensive Step-by-Step Guide

Pickl AI

JULY 8, 2024

Solutions and Best Practices to Overcome Complications In this section, you will look at techniques, tools, and best practices that can help you overcome common complications in building and maintaining data pipelines and ensure they are scalable, reliable, and performant.

Data Pipeline

Data Pipeline Data Quality Database Apache Kafka

Data Science Current

Introduction to Apache Kafka: Fundamentals and Working

A Detailed Guide of Interview Questions on Apache Kafka

Webinars

Trending Sources

22 Widely Used Data Science and Machine Learning Tools in 2020

Webinars

Streaming Machine Learning Without a Data Lake

Best Data Engineering Tools Every Engineer Should Know

Big data engineering simplified: Exploring roles of distributed systems

Predicting the Future of Data Science

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

Did Big Data Deliver Business Transformation & Improved CX?

Discover the Most Important Fundamentals of Data Engineering

Big Data Syllabus: A Comprehensive Overview

A Comprehensive Guide to the main components of Big Data

How data engineers tame Big Data?

Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Build Data Pipelines: Comprehensive Step-by-Step Guide

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