Closing the door to the library of lost data

Most companies are undergoing a transformation to “A data company that does (insert their company) better than anyone else.” Modern companies are not only data, digital, and cloud native, they are finding ways to differentiate themselves through their data and monetize it as an additional revenue stream. Furthermore, the only way to keep pace with the rapid advancements in AI and machine learning (ML) is to make strategic investments in stabilizing the underlying data infrastructure. But what happens if the immense amount of data stored today is not managed properly?

Imagine trying to find a specific book in a library, not knowing the location, title, or even the author. Oh, and there’s no resource or person to ask, so you go around asking someone else in the library for help, hoping they’ll point you in the right direction or just hand you a book. Similarly, unmanaged data buries itself in a dark corner of a “library,” but in most cases it doesn’t resemble the book it once was, and the author is unknown. This often happens through data silos, redundant or duplicate platform services, conflicting data stores and definitions, and more, all of which adds unnecessary cost and complexity.