Apache Storm is an advanced and distributed open source stream engine processing big data at an extremely high speed. Written in Clojure programming language, it is a real-time computational system which makes it easier to process unbounded streams of data. One of its advantages is that it can be used on any programming language. Built to accept tons of data flowing in with high speed from various sources, it analyses and publishes real-time updates to a UI or any other specified target place.
Apache Storm training will help you master its concepts including its architecture, installation, planning, and configuration. You will learn to leverage the power of Storm and use it for real-time processing of big data. The course also helps you get an insight on the way Storm interfaces with other frameworks like Kafka, Java, and Cassandra. The explosion of big data and the fact that organizations have realized the potential of using tools such as Storm to analyse it, ensures that Apache Storm experts will have great opportunities to contribute to these enterprises and become indispensable to them.
Many software companies face big data issues and to solve this they look forward to professionals who are talented and certified to manage such big data at a faster pace.
Getting an Apache Storm certification will ensure several benefits to the individual:
For companies looking for fast deliveries and high productivity in big data analytics, Apache Storm is the need of the hour. It has the following benefits.
Learn what is Big Data and relevant concepts, where it is used, and various types of data analytics
Understand the concepts of Storm architecture, use cases, & its usage in real-time stream processing
Learn how to set up Storm and what system configuration is needed to create various topologies
Get the knowledge on how to use spouts & bolts along with their mechanism and life cycle
Learn how to handle failures in Trident topologies & how to perform real-time computing in Storm
Get your concepts clear by working on real-time projects on Twitter, Spotify and travel websites