Organizations are adopt advanced artificial intelligence (AI)-enabled solutions at a growing rate. With data management challenges continuing to mount on technology teams, the technology decision-makers are realizing that without a firm data strategy provisioning enterprise-wide supply of data on demand, machine learning and AI adoption will remain just another set of buzz words. Tech Republic brought this interesting information to us in their article, “How to use data governance for AI/ML systems.”
The recent technological advances like big data, Internet of Things (IoT) and machine learning have necessitated further tuning of data governance practices throughout global businesses. As the trend toward self-service analytics and business intelligence (BI) continues, it will become apparent that data quality and data governance will occupy critical places in the organizational data strategy framework.
At the end of the day, content needs to be findable and, that happens with a strong, standards-based taxonomy. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies and associated rule bases for machine-assisted indexing.
Melody K. Smith
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