‘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