The explosion of data that comes with artificial intelligence (AI) has some concerned about the security and quality of that data. This interesting topic came to us from Barron’s in their article, “2020: Get Your Data House in Order.”
This is an unanticipated consequence of AI and data analytics popularity. Even though there is much fascination with data dashboards and other analytical tools to wow your clients with, if those results were based on incorrect data, the situation has gone south fast.
Big data doesn’t translate to quality data, nor does it mean volume. Most organizations understand this and are elevating data governance responsibilities on the priority ladder by creating a chief data officer role. Data accuracy and consistency across all technologies are part of this role.
Whether your organization is in the position to do this or not, the first step should be a data consistency audit. Data integrity has become a serious issue over the past few years and therefore is a core focus of many enterprises.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.