Real-time Big Data

Traditional analytics are usually a process for generating reports from structured data stored in an old-fashioned data warehouse. Big Data drives business values by creating competitive advantages and relevance from different sources of structured, semi-structured, and unstructured data. Analytical processes that used to run long hours or days are now reduced by an order of magnitude.

Real-time Big Data represents a convergence of science, engineering, and technology disciplines to collect, transform, store, process, analyze, and search massive data in real time. The trend is towards faster, intelligent, increasingly-automated, cost-effective, and high-quality processing of data that produces insights quickly and offers specific recommendations in the right context, resulting in greater sales and higher profits. Despite recent progress in the high-performance systems like trading and online advertisements, there are still a number of issues, barriers, pitfalls, and roadblocks in this maturing space.

A panel is organized in the upcoming IEEE Big Data Congress, with a group of industry gurus and field practitioners to share their views on the challenges, trends, use cases, industry implementations, compressed index, columnar storage,  in-memory index, SSD data, indexed map-reduce, etc.

For more information, please contact Tony Shan (blog@tonyshan.com) or leave your comments below. 

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