Apache Storm Online Training

Course Feature
  • Cost
    Paid
  • Provider
    Edureka
  • Certificate
    No Information
  • Language
    English
  • Start Date
    Self Paced
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    /
Next Course
5.0
6,000 Ratings
Learn how to process big data in real time with Apache Storm Online Training. This comprehensive course covers everything from the basics of big data processing to advanced topics like Kafka integration and transaction topologies. With hands-on exercises and practical case studies, you'll gain the skills needed to install and use Storm effectively. Whether you're a beginner or an experienced data professional, this course will take your knowledge to the next level. Don't miss out on this opportunity to become an expert in real-time big data processing. Enroll now!
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Course Overview

❗The content presented here is sourced directly from Edureka platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [September 05th, 2023]

Skills and Knowledge Acquisition:

Big Data Fundamentals: Students will gain an understanding of big data concepts and real-time big data processing, laying the foundation for working with Apache Storm.

Batch Processing vs. Real-time Processing: The course explores the differences between batch and real-time data processing, with a focus on the advantages of real-time processing.

Comparison with Hadoop and Spark: Participants will learn how Apache Storm compares to other big data processing frameworks like Hadoop and Spark, understanding its unique strengths.

Installation and Setup: Students will be guided through the installation process of Apache Storm, enabling them to set up their own Storm clusters.

Storm Components: The course covers the various components of Apache Storm, including spouts and bolts, and explains how they work together in data processing.

Topology Development: Participants will learn to create basic topologies using spouts and bolts, allowing them to build their own real-time data processing applications.

Kafka Integration: The course introduces Kafka, a popular distributed streaming platform, and how it can be integrated with Apache Storm for data ingestion and processing.

Advanced Topics: Students will explore advanced concepts such as Trident topologies and transaction topologies, expanding their knowledge of real-time data processing.

Practical Case Studies: The course includes practical case studies that demonstrate how Apache Storm is used in real-world scenarios, providing valuable insights and hands-on experience.

Contribution to Professional Growth:
This course offers significant contributions to professional growth:

In-Demand Skills: Proficiency in Apache Storm is highly sought after in industries that require real-time data processing, such as finance, e-commerce, and IoT, contributing to increased employability.

Competitive Edge: Learning to work with Apache Storm sets professionals apart in the field of big data and real-time analytics, making them more competitive candidates for job roles requiring these skills.

Enhanced Problem-Solving: Participants will develop problem-solving skills in the context of real-time data processing and complex data streams, enhancing their overall problem-solving abilities.

Suitability for Preparing Further Education:
The "Apache Storm Online Training" course is suitable for individuals preparing for further education in data engineering, real-time analytics, and big data processing:

Graduate Studies: Students pursuing advanced degrees in data science, computer science, or related fields can use this course as a foundation for deeper exploration of real-time data processing technologies.

Certification: Those planning to pursue certifications related to Apache Storm or big data technologies can benefit from this course as a preparation resource.

Professional Development: IT professionals looking to expand their knowledge of real-time stream processing and fault-tolerant systems can use this course to enhance their expertise and prepare for further career advancement.

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