What We Do

We incorporate a modern data analytics architecture and a domain-oriented data strategy to enable real-time analytics, predictive modeling, and seamless data integration across the student lifecycle.

Our scalable solutions are not just about adaptability and resource utilization. They also empower individual departments, enhance student success, and automate critical processes from recruitment through alumni engagement.

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Admissions & Enrollment

Utilize advanced data analytics to transform the admissions process. Implement machine learning models to analyze multi-year applicant data throughout the admissions cycle and develop recommendation engines that optimize candidate enrollment.

Implement predictive analytics pipelines to process demographic and recruitment performance data, forecast enrollment trends, predict yield rates for admitted students, and automate resource allocation for targeted recruitment efforts.

Student Journey Enhancement

Leverage historical and real-time student data to improve student success and retention. Utilize machine learning models to analyze applicant data during the admissions cycle and develop recommendation engines for optimizing candidate targeting and enhancing retention.

Establish predictive analytics pipelines to process demographic and recruitment performance data, forecast enrollment trends, identify at-risk students, and automate resource allocation for targeted interventions.

Advancement & Alumni Relations

Boost alumni engagement by utilizing data-driven strategies. Analyze alumni demographics and behaviors to develop dynamic persona models that will inform engagement strategies and messaging.

Strengthen relationship networks by identifying indirect connections among various groups, fostering these relationships to enhance commitment. Enhance donor interactions by matching donor profiles with personas and recommending the most suitable engagement.

           

Whitepaper: Unlocking the Potential of Data in Higher Education

Modern data platforms empower higher education institutions to integrate data from diverse sources, overcoming challenges like data silos and variety. This whitepaper discusses how, utilizing intelligent data lakes and marketplaces, universities can personalize learning, optimize resources, and accelerate research, ultimately driving student success and institutional effectiveness.

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