The big data ecosystem is constantly expanding, gravitating ever further from the four walls of the traditional centralized enterprise with a burgeoning array of external sources, services, and systems.
Capitalizing on this phenomenon requires horizontal visibility into data’s import for singular use cases—whether building predictive models, adhering to regulatory accords, devising comprehensive customer views and more—across a sundry of platforms, tools, and techniques.
The capacity to single-handedly avail organizations of the collective worth of such decentralized resources lies in the means of standardizing these data as though they were all in the same place, paradox notwithstanding. Accounting for the inevitable differences in schema, terminology, and data representations requires a data modeling uniformity across settings and sources alike.
Failure to do so prolongs the interminable journey towards data silos, regulatory penalties, and squander of data-centric investments.
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