At BLUEPRINT 4D 2026, Sathya Purusothaman and Thiemuli Nevhutalu from the University of Pretoria shared a practical and highly relatable session on building real-time admissions dashboards using OpenSearch and PeopleSoft Campus Solutions.

Their presentation was not just a technical walkthrough. It was a candid look at how one university tackled a common higher education challenge: transforming massive amounts of admissions and registration data into actionable, real-time insights that help staff make faster and better decisions during peak enrollment periods.

For institutions exploring OpenSearch dashboards in PeopleSoft, the session offered a roadmap grounded in real-world lessons, technical experimentation, iterative design, and user-centered thinking.

Why Real-Time Admissions Insights Became a Priority

The University of Pretoria operates one of the largest higher education environments in South Africa, supporting more than 55,000 students across nine faculties. Their admissions cycle creates intense operational pressure because undergraduate intake occurs once per year, with registration activity heavily concentrated in January and February.

During that short window, admissions teams need immediate visibility into application volumes, offers made, acceptances, registrations, and enrollment targets. Traditional reporting tools were not delivering the real-time responsiveness the business needed.

While the university already used Oracle Business Activity Monitoring and enterprise reporting tools for management-level analytics, those solutions were not designed for operational decision-making happening minute by minute during registration season.

That led the team to OpenSearch dashboards within PeopleSoft Insights.

Starting With User Stories Instead of Data

One of the strongest themes throughout the session was the team’s commitment to designing dashboards around business decisions rather than simply visualizing available data.

Instead of beginning with tables and fields, the project started with conversations about pain points. Admissions staff wanted to know:

• How many offers had been made
• Which students had accepted offers
• Which applicants had not responded
• Whether programs were meeting enrollment targets
• Which programs were over-registering or under-registering students

The presenters emphasized that the dashboard project succeeded because it focused on the decisions users needed to make, not just on displaying information.

That philosophy shaped every design choice that followed, from data mapping to index structure to visualization selection.

Designing Dashboards That Support Immediate Action

The initial release of the admissions dashboard included several operationally focused visualizations:

• Real-time admissions statistics
• Offer acceptance tracking
• Enrollment and registration targets
• Faculty-level registration monitoring
• Application response trends
• Drill-down application tables for direct action

Admissions administrators could immediately identify programs exceeding targets or falling behind. In some cases, the dashboards revealed that certain programs were significantly over-registering students before staff had visibility into the problem.

The dashboards also enabled outreach workflows. Staff could quickly identify applicants who had not responded to offers and follow up before losing potential enrollments.

One particularly valuable feature was the embedded data table visualization. Users could filter applications directly from the dashboard, open the corresponding application record, update statuses, and immediately see those changes reflected in the dashboard.

That tight feedback loop dramatically improved operational efficiency.

Solving the OpenSearch Index Design Challenge

A significant portion of the presentation focused on OpenSearch index design, which the presenters described as one of the most important and difficult aspects of the project.

The team ultimately chose a “one document per application” approach rather than organizing data by applicant. This structure simplified application counts, unique headcounts, and dashboard aggregation logic.

They also combined admissions and registration information into a single index instead of maintaining separate indexes. That decision helped keep the architecture simpler while supporting the blended reporting needs of admissions teams.

Equally important was deciding what not to include.

Because Campus Solutions admissions data spans numerous tables and customizations, the team intentionally limited indexed data to only the fields required for user stories, filters, and visualizations.

That disciplined approach improved performance and avoided unnecessary complexity.

Balancing Real-Time and Batch Processing

The presenters also shared practical lessons about balancing real-time indexing with overnight batch processing.

Some data updates — such as application status changes — were pushed to OpenSearch in real time. However, high-volume processes like automated ranking and admissions evaluations were handled through nightly incremental indexing.

With roughly 180,000 applications processed annually, attempting to index everything in real time would have created performance problems.

Instead, the team negotiated realistic expectations with business users. Batch ranking processes ran overnight, and dashboards were refreshed by the next morning. That compromise preserved system performance while still delivering highly responsive operational reporting.

The team also implemented monthly full loads for the most recent admissions cycles to maintain data accuracy.

Learning OpenSearch With AI Assistance

One of the session’s most memorable discussions centered around how AI tools accelerated development.

Purusothaman explained that transitioning from a traditional relational SQL mindset to OpenSearch’s JSON-based querying model was initially challenging.

To bridge the gap, he used tools like OpenAI’s ChatGPT and Claude as learning companions rather than code generators.

AI helped with:

• Recommending visualization types
• Explaining OpenSearch DSL queries
• Troubleshooting visualization errors
• Suggesting configuration approaches
• Interpreting OpenSearch documentation

The presenters stressed the importance of providing detailed context to AI tools, including PeopleTools and OpenSearch versions, because unsupported features in newer releases frequently caused inaccurate recommendations.

Perhaps most importantly, they approached AI as a teacher rather than blindly accepting outputs. They repeatedly tested, refined, and validated recommendations during the dashboard build process.

Security, Performance, and Scalability Lessons

The session also explored practical implementation considerations that many institutions will recognize.

Security was initially simplified by limiting dashboard access to admissions super users before eventually rolling out row-level security to faculty administrators.

Performance optimization became increasingly important as admissions cycles accumulated. Early dashboard versions lacked default filters, causing dashboards to retrieve multiple admissions years simultaneously. The team later implemented default admit-term filtering to improve responsiveness.

Infrastructure sizing was another valuable discussion point. The university currently operates a shared OpenSearch environment across four PeopleSoft applications, using clustered production infrastructure with failover support.

They also learned the importance of data archival strategies after an HCM recruitment dashboard overwhelmed storage capacity by indexing years of applicant data without purging historical records.

A Blueprint for Campus Solutions Innovation

One of the most compelling aspects of the session was its reminder that Campus Solutions institutions already possess the tools needed to begin building operational insights today.

Although Oracle has delivered fewer prebuilt dashboards for Campus Solutions compared to HCM and Finance, the presenters demonstrated that universities can successfully create highly impactful dashboards tailored to their own processes and data models.

Their advice was straightforward:

Start small. Focus on a genuine business pain point. Build around user decisions. Iterate continuously. Get the index design right. Use AI as a learning accelerator. And prioritize operational value over flashy visualizations.

For institutions struggling with admissions visibility, registration monitoring, or enrollment management, the session provided an excellent example of how OpenSearch and PeopleSoft Insights can move beyond static reporting and become true operational decision-making tools.

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