Data quality has never been more important. It is at the heart of the success of enterprise artificial intelligence (AI) and other emerging technologies. It remains the main source of challenges for companies that want to apply machine learning in their applications and operations. Venture Beat brought this interesting information to our attention in their article, “Why data remains the greatest challenge for machine learning projects.”
The concept “garbage in, garbage out” can easily be applied to the data processes used by companies to inform everything from hiring decisions to anticipating and meeting the demands of emerging markets. In either case, can they afford any misstep? As the volume of data generated by internal and external sources grows almost exponentially, organizations’ ability to assure its integrity becomes both more challenging and more important.
Making data accessible and of the highest quality is critical. Whatever you are searching for, it is important to have a comprehensive search feature and quality indexing against a standards-based taxonomy. Choose the right partner in technology, especially when your content – and quality – is in their hands. Access Innovations is known as a leader in database production, standards development, and creating and applying taxonomies.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Sponsored by Access Innovations, changing search to found.
