Exponentially growing data volumes create myriad challenges. Chief among them is the risk to data already stored in silos. If companies continue to operate in analytics environments with no central point of data access, all the new information being collected will exacerbate already fragmented views of the company’s business.
Not only will these organizations be challenged to extract the value from their existing data investments, but the stunted view could also expose them to unseen risks as new data continues to roll in.
That’s why a centrally governed semantic layer that is performant at scale against Big Data—and can readily accommodate new sources—is a growing use case for many organizations.