Skip to main content

Apache Beam | A Hands-On course to build Big data Pipelines

apache-beam-a-hands-on-course-to-build-big-data-pipelines
Udemy Coupon - Apache Beam | A Hands-On course to build Big data Pipelines
Build Big data pipelines with Apache Beam in any language and run it via Spark, Flink, GCP (Google Cloud Dataflow).

  • BESTSELLER
  • 4.5 (199 ratings)
  • Created by J Garg - Hadoop Real Time Learning
  •  English

Preview this Course - GET COUPON CODE

Description
Apache Beam is a unified and portable programming model for both Batch and Streaming use cases.

Earlier we could run Spark, Flink & Cloud Dataflow Jobs only on their respective clusters. But now Apache Beam has come up with a portable programming model where we can build language agnostic Big data pipelines and run it using any Big data engine (Apache Spark, Flink or in Google Cloud Platform using its Cloud Dataflow and many more Big data engines).

Apache Beam is the future of building Big data processing pipelines and is going to be accepted by mass companies due to its portability. Many big companies have even started deploying Beam pipelines in their production servers.

What's included in the course ?

Complete Apache Beam concepts explained from Scratch to Real-Time implementation.

Each and every Apache Beam concept is explained with a HANDS-ON example of it.

Include even those concepts, the explanation to which is not very clear even in Apache Beam's official documentation.

Build 2 Real-time Big data case studies using Beam.

Codes and Datasets used in lectures are attached in the course for your convenience.

Who this course is for:
Students who want to learn Apache Beam from scratch to its Live Project Implementation.
Data engineers who want to build unified & portable Big data processing pipelines.
Developers who want to learn a futuristic programming model for Big data processing.

100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Comment Policy: Please write your comments that match the topic of this page post. Comments containing links will not be displayed until they are approved.
Open Comments
Close Comment
-->