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How MDM Helps Higher Education Improve Student Success and Retention

post April 11, 2023

Master Data Management (MDM) can be a game-changer for higher education institutions that need to improve their operational efficiencies to improve the student lifecycle.  Higher Education Data Challenges Many higher education institutions are grappling with challenges across the entire student lifecycle. Operating models are under pressure, with the current slide in enrollment being noted by […]

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National Student Clearinghouse

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Tackling the challenges of governance, master data and data quality — NSC wanted to align MDM to their corporate strategy of improving customer support with accuracy of data and records on all learners, while migrating data from legacy systems to the cloud.

Higher Education

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Schedule Your Master Data Management Demo Higher Education Master Data Management Made Easy Give every department access to secure, centralized data. Our higher education Master Data Management software has a business-driven interface that lets users discover, understand, and apply data quickly. Product Features See How You Can Measure ROI in Under 12 Weeks : Comprehensive […]

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5 Ways to Elevate Master Data Management in Higher Education

post September 15, 2023

Utilizing a unified data platform, higher education can successfully tackle the challenges of governance, master data, and data quality that can help leaders make lasting change.

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9 Key Aspects of a Master Data Management Strategy

post June 20, 2023

Master Data Management (MDM) organizes, categorizes, and synchronizes an organization’s data to create a single point of reference, or ‘golden record.’ A solid MDM strategy is the backbone of any data-driven organization, as it ensures reliable and quality data, thereby enabling better business decisions. What Is a Master Data Management Strategy? A Master Data Management […]

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Reducing Errors and Improving Accuracy with Data Integration

post April 25, 2023

The main objective of data integration is for your organization to produce clean, consolidated data sets that meet the needs of information users. In other words, that data should be in such a state that it helps them to devise solutions to achieve their goals accurately and quickly.