HI, Honolulu - Waterfront

7 Waterfront Plaza, 500 Ala Moana Blvd. Suite 400, Honolulu, united states, 96813
onolulu business center is located at 7 Waterfront Plaza in the commercial district of Kakako. It sits in the midst of the W...

HI, Kapolei - Waterfront

7 Waterfront Plaza, 500 Ala Moana Blvd., Suite 400,, Honolulu, united states, 96813
Waterfront Plaza is located along the vibrant Ala Moana Boulevard corridor linking Waikiki, Honolulu's Central Business Distr...

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Apache Storm

28 Hours
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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Testimonials (3)

Las explicaciones eran muy buenas, si bien algunas preguntas pudieron ahorrarse si se hubieran tocado esos puntos al inicio de los temas se notó un buen dominio y experiencia en el tema.

Alan Jaime Rodríguez García - BANCO DE MEXICO
Course - Stream Processing with Kafka Streams

Recalling/reviewing keypoints of the topics discussed.

Paolo Angelo Gaton - SMS Global Technologies Inc.
Course - Building Stream Processing Applications with Kafka Streams

Sufficient hands on, trainer is knowledgable

Chris Tan
Course - A Practical Introduction to Stream Processing

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