Real-time Data360 on Apache Spark

‘Data360’ is a new term and is being used to represent a one-stop shop for all your Big data processing needs.

Enterprise IT teams are faced with the challenge of choosing one vendor for data ingest, another for data wrangling, a third one for machine learning/analytics and yet another for visualization.

Shouldn’t it be really easy to do all the modern data management in a unified way, especially if you have already chosen to go with Spark as your Big Data platform? It can be; however the powerful usage of Spark still needs very skilled Scala/Java programmers. A different approach is needed.

During this webinar you will get to know about:

  • A powerful all-in-one Apache Spark strategy for the enterprise and an implementation approach for end-to-end big data analytics processing

  • The elements of a real-time Data360 solution – Ingest, Cleanse, Transform, Blend, Analyze, Load and Visualize

  • A combination of tools and tactics used for Data360 on streaming and historical data, using Apache Spark and Apache Spark Streaming

  • How use cases like anomaly detection, customer 360, IoT and log analytics, fraud and security analytics and many more can be achieved using this approach


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