TECHNICAL FIELD

Embodiments of the present application relate generally to processing and analyzing a super plurality of data in a data-intensive complex computing architecture. In particular, the embodiments relate to systems, methods, computer program products, and apparatuses for ingesting and analyzing a super plurality of data, identifying intelligence information, and identifying stories therefrom.

BACKGROUND

In the normal course of operations, entities create considerable to very large amounts of electronic data resulting from their operations. In some cases, the amount of electronic data generated can be in the tens of thousands to millions of units of data per day thereby resulting in extremely large data sets (e.g., big data), which can be unstructured and structured. Using big data platforms, some of these entities seek to leverage their big data to obtain beneficial insights and this is done, mainly, by utilizing the big data platform to store the large volume of data and organize the data in a format that is searchable via queries.

A challenge with this model of using the big data platform, however, is that in order to obtain the useful insights that the entities envisions to obtain, an IT administrator or other administrator of the big data platform must be able to run appropriate queries against the data in the platform. Thus, in such a model, the insights may only be useful if the queries against the data are good.

To assist in the use of big data platforms, some software applications are implemented in big data platforms to analyze the incoming data. In such instances, to determine useable data, these applications apply substantial analysis against each unit of datum of incoming data, organize the data, and potentially run automated queries thereon to provide insights or information to the administrator. However, analyzing each unit of datum of these very large datasets in this manner usurps significant computing resources and in turn, delays the data processing and insight determination due to overuse of the computer processors, memory, and other technical computing elements of the big data platform. Further, there is no guarantee that the queries applied by the software applications will, in fact, identify useable data and return useful insights.

Thus, there is a need in the data-intensive complex computing architecture field to create new and useful systems, methods, and apparatuses to be implemented in a data-intensive complex computing architecture for processing big data, identifying useful data, and generating meaningful and exploratory intelligence therefrom. The embodiments of the present application provide such new and useful systems, methods, computer program products, and apparatuses.

