Real Time Analysis using Apache Storm Course Overview

Real Time Analysis using Apache Storm Course Overview

The "Real Time Analysis using Apache Storm" course offers a comprehensive dive into the world of Big Data and its practical applications, particularly focusing on real-time stream processing. Learners will start by gaining a foundational understanding of Big Data and its significance across various industries, along with different types of data analytics. The course then introduces Apache Storm, elucidating its architecture, use cases, and unique value in handling real-time data streams.

As participants progress, they'll tackle the practical aspects of Storm Installation and Configuration, learning about different nodes and running modes, as well as the nuances of stream grouping. In-depth exploration of Spouts and Bolts follows, where learners will comprehend the basic building blocks of a Storm topology, messaging reliability, as well as integration with external systems like Kafka.

Finally, the course delves into Storm Trident, an extension of Storm that provides high-level abstraction for doing stateful stream processing in a more straightforward and flexible manner. By the end of this course, students will have the knowledge to design, configure, and implement robust real-time data processing solutions using Apache Storm, making them valuable assets in the field of Big Data analytics.

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  • Live Training (Duration : 16 Hours)
  • Per Participant
  • Classroom Training fee on request

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

  • Basic Computer Knowledge.

Target Audience for Real Time Analysis using Apache Storm

The Real Time Analysis using Apache Storm course is designed for IT professionals focused on big data and real-time analytics.


  • Data Engineers
  • Big Data Architects
  • Software Developers specializing in big data processing
  • IT Professionals with a focus on data streaming and event processing
  • System Administrators responsible for managing big data platforms
  • Data Scientists looking to leverage real-time analytics
  • Technical Project Managers overseeing big data projects
  • DevOps Engineers involved in continuous data processing systems
  • Database Professionals wanting to expand their skill set into big data technologies
  • Students and Researchers in computer science with an interest in distributed computing systems


Learning Objectives - What you will Learn in this Real Time Analysis using Apache Storm?

Introduction to Course Learning Outcomes

Gain expertise in processing Big Data in real-time with Apache Storm, understanding its architecture, components, and how to design and deploy stream processing solutions effectively.

Learning Objectives and Outcomes

  • Understand the core concepts of Big Data, its significance, and the various analytics techniques used in the industry.
  • Grasp the fundamentals of Apache Storm's architecture, including its components and their roles in real-time data processing.
  • Learn the practical use cases of Apache Storm and how it is applied in different industries for real-time analytics.
  • Master the installation and configuration of Apache Storm, including setting up Nimbus, Supervisor, and Worker nodes.
  • Acquire knowledge of different running modes in Storm, such as Local and Remote modes, and the various stream grouping strategies.
  • Comprehend the function and implementation of Spouts in Apache Storm for data emission and the techniques for fetching data.
  • Delve into Bolts, the processing units in Storm, and learn how to create reliable and unreliable messages within a topology.
  • Gain hands-on experience in developing a basic topology using Spouts and Bolts, and understand how to monitor the topology using Storm UI.
  • Explore Trident, a high-level abstraction for doing stream processing on top of Storm, and understand how to design transactional topologies.
  • Learn how to integrate Storm with other systems such as Kafka for reliable message processing and enhanced capabilities.
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