(Big Data TechCon 2015)
Enterprises are challenged today with providing continuous assimilation and correlation of data across a wide variety of big data systems such as HDFS and EDWs; open source layers such as Kafka and Flume; and transactional systems such as Oracle and MySQL. Yet immediate ingestion, aggregation and continuous correlation across these data systems is required to deliver the operational metrics, in-memory processing, realtime dashboards, and live reports to end users for actionable realtime analytics.
Watch this session to learn how to ingest, filter, aggregate, correlate and visualize data from all major Big Data sources — as data is being produced/events occur — using a SQL/Java-based interface. See how aggregated result sets can be persisted in an integrated Elastic Search tier for efficient indexing and fast querying.