Harmonizing big data with an enterprise knowledge graph

Franz’s CEO, Jans Aasman, recently wrote the following article for InfoWorld.

In addition to streamlining how users retrieve diverse data via automation capabilities, a knowledge graph standardizes those data according to relevant business terms and models

One of the most significant results of the big data era is the broadening diversity of data types required to solidify data as an enterprise asset. The maturation of technologies addressing scale and speed has done little to decrease the difficulties associated with complexity, schema transformation and integration of data necessary for informed action.

The influence of cloud computing, mobile technologies, and distributed computing environments contribute to today’s variegated IT landscape for big data. Conventional approaches to master data management and data lakes lack critical requirements to unite data—regardless of location—across the enterprise for singular control over multiple sources.

The enterprise knowledge graph concept directly addresses these limitations, heralding an evolutionary leap forward in big data management. It provides singular access for data across the enterprise in any form, harmonizes those data in a standardized format, and assists with the facilitation of action required to repeatedly leverage them for use cases spanning organizations and verticals.

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