Master Big Data Realtime Streaming

Learn the Core Concepts of Big data Realtime Streaming Analytics and also work with Hands On Examples

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Description

Getting real-time insights from huge volumes of data is very important for a majority of companies today.

Big data Real-time streaming is used by some of the biggest companies in the world like e-commerce companies, Video streaming companies, Banks, Ride-hailing companies, etc.

Knowing about the concepts of realtime streaming and the various realtime streaming technologies will be a great addition to your skillset and will enable you to build some of the most cutting-edge solutions that exist today.

We have created this Hands-On Course so that you get a good understanding about how realtime streaming systems can be built

This course will ensure that you get a hands-on experience with Apache Kafka, Apache Flink, Spark Streaming, Kafka Streams, Apache Pinot, Apache Druid, and Apache Superset.

This course covers the following topics

  • An Introduction to Kafka with hands-on Kafka setup

  • Understanding basic transformations and aggregations which can be done in a real time system

  • Learn how transformations and aggregations can be done using Apache Flink with hands-on coding exercises

  • Learn how transformations and aggregations can be done using Spark streaming with hands-on coding exercises

  • Learn how Kafka streams can be used to perform transformations and aggregations with hands-on coding exercises

  • Ingest data into Apache Pinot which is an OLAP technology

  • Ingest data into Apache Druid which is also an OLAP technology

  • Using Apache Superset to create some insightful dashboards

If you are interested in learning how all these technologies can be connected together to build an end to end real-time streaming system, then this course is for you.

What You Will Learn!

  • Learn designing an end-to-end Real-time Streaming pipeline for Big Data using latest technologies.
  • Understand the different components in Big Data streaming pipeline.
  • Use Kafka as the connecting tool between ETL components in the real-time streaming pipeline.
  • Use Apache Flink, Spark Streaming and Kafka Streams to perform different transformations and aggregations.
  • Use Druid and Pinot as OLAP technologies in the streaming pipeline.
  • Use Superset to visualize the real-time incoming data stream to explore and visualize the transformed data.
  • Hands-on Practicals helping you build all the components and forming a complete end-to-end pipeline.
  • Learn multiple technologies used in Real-time Streaming pipelines, and you can use the one that better suits your use-case.

Who Should Attend!

  • Students who want to learn building real-time streaming pipelines from SCRATCH to its Live Project Implementation.
  • Students who want to learn latest technologies that are used in Big Data Engineering.
  • Developers who want to learn different well-known tools to build streaming pipelines.
  • Students who want to pursue and grow career in Data Engineering.