The first successful big data technology was enterprise data warehouses that implement massively parallel processing, scale to the petabytes, handle batch and real-time latencies with equal agility, and provide connectors to structured and unstructured sources.
And the reality is, there is more batchprocessing and post-process reporting in Big Data applications (vs. real-time capabilities) than insiders want to admit.
Risk is moving to real-time in trading limits and some other areas, but overall risk is still mostly end of day batchprocessing and pulls from multiple sources of data.