Real-time Data360 on Apache Spark

'Data360' is a new term and is being used to represent a one-stop shop for all your 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 this in a unified way, especially if you have already chosen to go with Spark as your 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 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

Speakers:

Anand Venugopal,
Product Head, StreamAnalytix

Punit Shah,
Solution Architect, StreamAnalytix