DARE Phase 3: Advancing UCF’s Data & AI Capabilities
Since its initial go-live in Spring 2022, the Data and Analytics Reporting Ecosystem (DARE) has evolved through three strategic phases, culminating in December 2024 with the completion of Phase 3. This initiative, powered by Microsoft Azure and developed by UCF’s Analytics and Integrated Planning team in partnership with Midtown Consulting Group (MCG), represents a transformative leap in data architecture, analytics, and machine learning applications within higher education.
From Vision to Implementation: The Evolution of DARE
DARE was established as a critical part of the UCF Data and Analytics Strategy. This strategy outlined a bold vision to “create an environment that maximizes the value of data,” with a key objective to “develop and implement a university-wide scalable cloud data warehouse, reporting and analytics platform.” DARE modernized UCF’s enterprise data environment by addressing data fragmentation across institutional systems. Its phased development reflects a progression from foundational data management to AI-driven decision-making.
Importantly, the DARE project aligned with priority initiatives from UCF’s overall strategic vision: upgrading IT infrastructure to enhance service excellence, using predictive analytics in pursuit of student success and well-being, and strengthening job-fit and the collective capabilities of staff.
Phase 1: Establishing Data Lake Architecture & Security – Implemented Azure Data Lake with a strong security framework to support the Knight Vision Program, consolidating legacy system data for structured archiving and retrieval via Power BI.
Phase 2: Lakehouse for Integrated Data & Reporting – Expanded the Data Lake to serve as a centralized repository for historical and transactional data, ensuring efficient data access and structured reporting.
Phase 3: Lakehouse for Operational Data & AI-Powered Insights – Built a Lakehouse architecture to support live transactional data ingestion, automate state filings (SUDS reports), process reports, and compliance reporting. Integrated PeopleSoft Campus Solutions data and deployed machine learning models for predictive analytics, including retention, persistence, and course seat forecasting.
“The DARE program demonstrates the power of strategic data transformation. Each phase brought us closer to creating a unified system that’s not only efficient but scalable for future growth.”
— Pete Able, MCG Consultant
By evolving from a centralized data lake to an integrated Lakehouse and, ultimately, an AI-driven analytics hub, DARE has enabled UCF to transform data into actionable insights that drive institutional strategy.
Transforming Higher Education Data with AI & Automation
Higher education institutions often struggle with fragmented data spread across siloed systems, limiting their ability to synthesize insights across key areas such as student enrollment, retention, and resource allocation. Without a centralized data strategy, institutions face inefficiencies in cross-functional analysis, limitations in institutional reporting, and difficulties in forecasting key academic trends.
DARE was designed to resolve these issues by creating a unified data environment that automates reporting, integrates live data streams, and leverages predictive analytics for proactive decision-making. The platform now supports:
- Automated SUDS filings and process reports, ensuring compliance and streamlining mandatory state reporting.
- Historical data archiving for improved trend analysis and institutional benchmarking.
- Operational Data Store for core student data to leverage AI and ML models for student and campus insights
Innovative Solutions & The Future of Data at UCF
One of the standout features of DARE is its Power BI-driven data orchestration, which allows UCF administrators to manage data pipelines, ingestion processes, and error resolution without requiring advanced programming expertise. The integration of Azure Dataflows Pipelines and a Medallion Architecture ensures a seamless and scalable data management process, enabling more efficient handling of institutional data.
“Our collaboration with UCF has been incredibly rewarding. We’ve seen how the DARE platform is already transforming their approach to analytics, enabling timely insights that directly impact student outcomes.”
— Michael Morris, Data & AI Solutions Architect at MCG
The platform’s AI-driven forecasting models provide critical insights into student progression, offering a predictive lens into enrollment patterns, course demand, and student outcomes.
- Graduation Readiness Models – Uses historical and real-time course data to identify students who may require additional advising or intervention.
- Retention & Persistence Forecasting – Predicts student retention trends and at-risk populations.
- Course Seat Forecasting – Optimizes course scheduling and seat availability planning to align with enrollment patterns.
As DARE transitions into its next phase, UCF can focus on exploring opportunities with Microsoft’s latest features and releases, such as Fabric, while also expanding data accessibility across the institution. MCG’s comprehensive training programs have equipped UCF teams with the tools to manage and scale AI and analytics functions independently. Future initiatives will further expand datasets to promote a university-wide culture of strategic data use and innovation.
The DARE environment leverages Microsoft’s powerful suite of AI products, enabling UCF’s enterprise analytics team to build, refine, and optimize predictive models across the student lifecycle – from prospective students for admission to postgraduate degree earners. The team can also develop more prescriptive models to pursue intervention strategies for student success and well-being in line with the university’s strategic vision.
With DARE now serving as a centralized analytics hub, UCF is well-positioned to lead the next generation of data-driven higher education strategies that enhance student outcomes and institutional efficiency.
About MCG
Founded in 2004, Midtown Consulting Group (MCG) is a management consulting firm headquartered in Atlanta, GA with clients across the United States. Our diverse team of experts are committed to delivering modern end-to-end data and AI solutions that extend, predict, and prescribe organizations’ potential. We believe that Generative AI, including ChatGPT, will impact every aspect of business, learning, and human interactions. Organizations who adopt sustainable data and AI platforms will improve how they run, grow, and optimize their organizations’ productivity. Our experts are the backbone of our company; they innovate using technology to continually create optimal solutions for our clients. For more information, click here.