Analytics is used in a higher education environment to analyze various collected data points to gain insight and make informed decisions about complex issues. Specific areas include academic analytics, business intelligence, and learning analytics. University World News brought this interesting information to our attention in their article, “Taking the next step with data: It’s the smart thing to do.”
Today’s higher education leaders face many challenges, but by incorporating intelligent data analytics into their teaching and learning practices and day-to-day operations, institutions have the potential to grow student enrollment, transform learner experiences, and significantly improve student retention and completion rates.
Universities can use predictive analytics models to help with several agendas, from improving recruitment and retention to meeting students’ needs. Combined with real-time data analytics, predictive models can use stream processing to calculate what might happen in the future, but at a faster pace.
At the end of the day, data 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
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Sponsored by Access Innovations, changing search to found.
