Online or onsite, instructor-led live Apache Storm training courses demonstrate through interactive hands-on practice how to install and configure Apache Storm, then develop and deploy an Apache Storm application for processing big data in real-time.
Apache Storm training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Dresden onsite live Apache Storm trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located at Weißeritzstrasse 30 in Dresden. Our spacious t...
Overview
Our training facilities are located at Weißeritzstrasse 30 in Dresden. Our spacious training rooms are located directly west of Dresden's old town and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the tram stop Kongresszentrum and the A17 motorway is also easily accessible.
Parking
The Mitte multi-storey car park, right around the corner, offers guarded parking spaces.
Local Services
Within walking distance is the Leonardo Hotel Dresden Altstadt, other hotels and a variety of restaurants are also nearby.
Apache Storm is a distributed, real-time computation engine used for enabling real-time business intelligence. It does so by enabling applications to reliably process unbounded streams of data (a.k.a. stream processing).
"Storm is for real-time processing what Hadoop is for batch processing!"
In this instructor-led live training, participants will learn how to install and configure Apache Storm, then develop and deploy an Apache Storm application for processing big data in real-time.
Some of the topics included in this training include:
Apache Storm in the context of Hadoop
Working with unbounded data
Continuous computation
Real-time analytics
Distributed RPC and ETL processing
Request this course now!
Audience
Software and ETL developers
Mainframe professionals
Data scientists
Big data analysts
Hadoop professionals
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
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