Data’s intrinsic value doesn’t always pop out at you. It might take considerable work to distill useful insights from today’s big data sets. Sometimes automated tooling is necessary to reveal what the data truly signifies.
Data portfolio management refers to the process of harnessing your information resources for business insight. What it involves are the nitty-gritty tasks of cataloging, annotating, indexing, and otherwise managing it all so that the most valuable items rise to the surface.
Some refer to this process as “curation.” Whatever you call it, more enterprises are embracing cataloging solutions to reveal insights that would otherwise stay buried in their big-data portfolios. As noted recently by Alation, today’s business analysts and information stewards can’t do their jobs effectively without the ability to rapidly search, query, and share data-driven insights.
Wikibon believes that catalog-driven curation should be instituted as a standard capability in most big-data environments. In addition, users should seek out big data cataloging tools that use rich metadata, high-powered visualization, and artificial intelligence (AI). These sophisticated technologies are an important element in any curational infrastructure to help users rapidly contextualize analytic insights that combine data ingested from increasingly complex hybrid clouds. AI enables greater automation of the curation pipeline in big data environments.
Digital business success depends on big-data cataloging as key application infrastructure. As Peter Burris stated in this recent Wikibon prediction, digital businesses in this new era will use these and other tools for harnessing “data as an asset.” More than that, these cataloging tools provide an application framework within which to better assess the value of all the data capital in your enterprise portfolio, in line what Peter said on a previous occasion.
In 2018 and beyond, Wikibon expects to see more solution providers incorporating AI to drive the continuous discovery, review, refinement, analysis, tagging, recommending, and other curational tasks across complex big data collections. Please check out this George Gilbert research from last year in which he discusses the larger role that big data catalogs play in a comprehensive big-data backplane from a growing range of solution providers.
