What is the impact of the limitations of traditional approaches to advanced analytics on big data?
The performance and latency problems of traditional data architectures and systems are so severe that application developers and analysts are forced to reduce “big data” to “small data” via aggregations, windowing, or sampling before performing analysis. This compromises the quality and depth of their analysis, resulting in sub-optimal decisions and lost revenue opportunities.
