Building Big Data Applications with Kapow

With the size of datasets increasing steadily for all organizations, spreadsheet data extraction and aggregation has become a more cumbersome task. Kapow, with their recently released Kapow Enterprise 9.2, hopes to alleviate that frustration with things they call “Kapplets” that aid in the building of big data applications that can be designed for data extraction optimization.

According to a study conducted by Ventana Research, usability is a significantly important aspect of information and big data applications for 54 percent of organizations, the most of any factor. Reliability came in at a close 2^nd with 46 percent while functionality took 3^rd with 42 percent. Kapow reportedly took note of these figures in the developing of Kapow Enterprise 9.2.

Per Ventana’s Mark A. Smith, Kapow focused on integration across all business processes to facilitate information movement within an organization. Kapow uses instruments they call Kapplets to automate said integration.

Version 9.2 reportedly has updated the Kapplets such that they execute “robots,” which essentially work as workflow schedulers. “[Kapow’s robots] can be executed in parallel as specific workflows, scheduled at any time and are user-defined to perform tasks that are linked by a workflow to get some end-state view of information,” Smith noted.

These “robots” also foster internet information unification. Specifically, an end user can hypothetically design a robot for a particular processing job, which would then gather relevant information from the institution’s servers as well as the internet, aggregate it, and deliver it to the business user.

Further, these designed ‘robots,’ which are essentially mini-applications, are reportedly available to all end users within the organization such that a new design doesn’t have to be created for similar additional queries.

The ability to recall these various designs speaks to that necessary degree of usability and simplicity. Bolstering that notion is Kapow’s reported ability to extract data from spreadsheets and deposit them for institutional use in on-site or cloud deployments.

Smith believes Kapow has the chops to position itself well in the BI management game, with the next step being mobile integration. “I hope,” Smith said, “Kapow will advance to support complete cloud computing deployments where integration across the Internet can be automated and leveraged for access even from mobile technologies.” It will be interesting to see how Kapow fares and if Smith is correct in the months ahead.

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