Remove Big Data Tools Remove Cloud Remove Kafka
article thumbnail

Top 21 Big Data Tools That Empower Data Wizards

ProjectPro

Well, in that case, you must get hold of some excellent big data tools that will make your learning journey smooth and easy. Table of Contents What are Big Data Tools? Why Are Big Data Tools Valuable to Data Professionals? Why Are Big Data Tools Valuable to Data Professionals?

article thumbnail

100+ Kafka Interview Questions and Answers for 2025

ProjectPro

Your search for Apache Kafka interview questions ends right here! Let us now dive directly into the Apache Kafka interview questions and answers and help you get started with your Big Data interview preparation! What are topics in Apache Kafka? Kafka stores data in topics that are split into partitions.

Kafka 45
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Apache Spark on Azure: When Big Data Meets Cloud

ProjectPro

78% of the employees across European organizations claim that the data keeps growing too rapidly for them to process, thus getting siloed on-premise. So, how can businesses leverage the untapped potential of all the data that is available to them? The answer is-Cloud! as needed for big data processing.

article thumbnail

Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

A powerful Big Data tool, Apache Hadoop alone is far from being almighty. Currently, the framework supports four options: Standalone , a simple pre-built cluster manager, Hadoop YARN, which is the most common choice for Spark, Apache Mesos , used to control resources of entire data centers and heavy-duty services; and.

article thumbnail

30+ Data Engineering Projects for Beginners in 2025

ProjectPro

In 2024, the data engineering job market is flourishing, with roles like database administrators and architects projected to grow by 8% and salaries averaging $153,000 annually in the US (as per Glassdoor ). These trends underscore the growing demand and significance of data engineering in driving innovation across industries.

article thumbnail

A Data Engineer’s Guide To Real-time Data Ingestion

ProjectPro

Data Collection The first step is to collect real-time data (purchase_data) from various sources, such as sensors, IoT devices, and web applications, using data collectors or agents. These collectors send the data to a central location, typically a message broker like Kafka.

article thumbnail

Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Consequently, data engineers implement checkpoints so that no event is missed or processed twice. It not only consumes more memory but also slackens data transfer. Modern cloud-based data pipelines are agile and elastic to automatically scale compute and storage resources.