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For many colleges and universities, Workday serves as the operational backbone for finance, human resources, payroll, planning, and student administration. It modernizes processes and creates a strong foundation for institutional operations. 

As institutions mature in their digital transformation journey, however, leaders often begin asking broader questions: 

  • Which students need support before they disengage? 
  • Which academic programs are driving institutional success? 
  • How should workforce strategies evolve alongside enrollment shifts? 
  • Where should resources be invested to maximize impact? 
  • How can AI support better decision-making? 

Answering these questions requires more than operational data alone. It requires a trusted foundation that connects information across the institution and turns it into actionable insight. 

At EDUCAUSE 2026, one of the most important conversations in higher education is not simply about systems. It’s about how institutions connect data to improve outcomes, strengthen planning, and prepare for the future of analytics and AI. 

Below are six common use cases Avaap sees as institutions look to maximize the value of their Workday investment, connect data across the institution, and support stronger decision-making. 

1. Student Success Analytics and Retention Insights 

Student data often lives across CRM, advising, learning management, financial, and student systems, making it difficult to identify risk factors early and provide proactive support. 

By creating a connected view of the student journey, institutions can gain insights into: 

  • Retention and persistence trends 
  • Student engagement patterns 
  • Financial risk indicators 
  • Advising effectiveness 
  • Opportunities for earlier intervention 

Xavier University: A Student 360 Approach 

Xavier University partnered with Avaap to unify Workday and other institutional data sources, creating a centralized foundation for student persistence analytics. The result was improved visibility into retention trends, reduced manual reporting, and more informed decision-making across student success initiative.

2. Academic Program Performance and Strategic Planning 

Academic leaders need visibility into enrollment, program demand, faculty workload, student outcomes, and financial sustainability. Yet that information often resides across multiple systems. 

A connected analytics foundation supports: 

  • Program demand analysis 
  • Faculty workload planning 
  • Program-level financial insights 
  • Student progression tracking 
  • Future investment decisions 

With a shared source of truth, institutions can spend less time gathering information and more time evaluating strategic opportunities. 

3. Financial Planning, Forecasting, and Executive Reporting 

Boards, presidents, provosts, and CFOs need timely visibility into institutional performance. However, critical information often spans finance, enrollment, workforce, and planning systems. 

Bringing these data sources together helps support: 

  • Budget-to-actual reporting 
  • Multi-year forecasting 
  • Enrollment impact analysis 
  • Strategic planning initiatives 
  • Executive and board dashboards 

This enables leaders to move beyond static reports and make decisions with greater confidence. 

4. Athletics Analytics, Compliance, and Institutional Impact 

Athletics data often spans multiple systems, creating challenges for reporting, compliance, and strategic planning. 

A unified view can support: 

  • NCAA reporting requirements 
  • Title IX reporting 
  • Student-athlete success initiatives 
  • Athletic program analysis 
  • Institutional planning and investment decisions 

Connecting academic, financial, and operational data creates a more complete understanding of athletics’ impact across the institution. 

5. Workforce Analytics and Position Management 

Workforce decisions are increasingly influenced by enrollment trends, budget priorities, and institutional strategy. 

Connecting workforce data with broader institutional information helps leaders better align staffing decisions to organizational needs and supports: 

  • Enrollment-driven workforce planning 
  • Program expansion initiatives 
  • Financial planning efforts 
  • Staffing and vacancy analysis 
  • Long-term institutional strategy 

6. Institutional Benchmarking and Competitive Analysis 

Many institutions are exploring predictive analytics, AI, and intelligent automation. Success begins with trusted, connected, and governed data. 

A modern data foundation can help institutions: 

  • Prepare for AI and machine learning initiatives 
  • Improve data governance and stewardship 
  • Increase confidence in reporting 
  • Reduce manual processes 
  • Support advanced analytics at scale 

As AI adoption accelerates across higher education, institutions with strong data foundations will be better positioned to innovate and realize value from emerging technologies. 

Building the Future of Higher Education Analytics 

The future of higher education analytics is more than reporting. It is about creating trusted insights that support student success, strengthen financial sustainability, improve institutional effectiveness, and prepare institutions for the opportunities AI will bring. 

As colleges and universities continue to modernize operations and maximize technology investments, many are discovering that their greatest opportunities lie not within any single system, but in their ability to connect data across the institution. Finance, HR, student, enrollment, advancement, learning management, and operational data each provide part of the story. Bringing those pieces together creates a clearer picture of institutional performance and supports more informed decision-making.  

At EDUCAUSE 2026, conversations around analytics, data strategy, institutional effectiveness, and AI readiness will continue to evolve. Institutions that can create trusted, connected data ecosystems will be better positioned to improve outcomes, accelerate decision-making, and maximize the value of their technology investments. 

As a Snowflake Elite Partner with deep higher education and Workday expertise, Avaap helps colleges and universities connect data across institutional systems, improve visibility into performance, and build scalable foundations for analytics and AI. Avaap helps institutions move beyond data consolidation to outcomes that matter.  

Attending EDUCAUSE 2026? Connect with Avaap to discuss how leading institutions are using Snowflake and modern data platforms to strengthen planning, advance analytics, and create a foundation for the next generation of AI-enabled innovation.

Schedule time to connect 

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Snowflake Summit 2026 brings together a wide range of sessions across AI, data engineering, and analytics, showcasing how the platform is being applied and extended in real-world environments. 

For Avaap, this year’s Summit is about how organizations are putting Snowflake to work: applying AI in real workflows, enabling teams with the right tools, and doing it in a way that’s governed and sustainable. As a consulting partner focused on helping higher education, government, and nonprofit organizations turn data investments into measurable outcomes, these are the conversations we pay closest attention to.

Below are a few sessions our team is especially looking forward to—both for what they demonstrate and the practical discussions they tend to spark.

1. Public Sector AI in Action at Snowflake Summit: Ohio Department of Taxation

Session: Ohio Tax: Call Center Analytics, Call Transcription and Agentic Workloads (AI230) 
Speaker: Budwhite Zhang, CDO and Deputy CIO, State of Ohio Department of Taxation 
Date & Time:  Monday, June 1 | 4:00–4:45 PM PDT 

This session offers a clear example of AI being applied within a regulated public sector environment. The Ohio Department of Taxation uses Snowflake Cortex to analyze call center transcripts, improve service consistency, and better understand taxpayer needs. 

What stands out is how directly this connects AI capabilities to an operational workflow — turning unstructured conversations into structured, usable insight. It’s the type of implementation that often becomes a foundation for additional use cases, from service optimization to fraud detection. 

Why we’re interested: 

  • A real-world application of AI in a government setting  
  • Practical use of unstructured data to drive outcomes  
  • A repeatable pattern that can scale across use cases  

2. Extending Snowflake with AI Apps and Analytics Workflows

Session: The Builder’s Guide to Sigma AI Apps: Workflows, Cortex Agents and AI Functions (BI214) 
Speaker: Senior Solution Engineer, Sigma 
Date & Time: Wednesday, June 3 | 1:00–2:30 PM PDT 

One of the themes we expect to see across Summit is how Snowflake’s capabilities are extended through its partner ecosystem. This session is a strong example of that in practice. 

Using Sigma alongside Snowflake Cortex, attendees will build a “Sales Pipeline Analyzer” that processes unstructured sales transcripts, extracts insights like deal health and risk, and writes structured outputs back into Snowflake. From there, workflows trigger notifications and dynamically update dashboards. 

It’s a hands-on look at how partner technologies and Snowflake work together to move beyond analysis and into action — enabling AI applications that interact with data, systems, and users in real time. 

Why we’re interested: 

  • Demonstrates how Snowflake is extended through partner tools like Sigma  
  • Shows how AI workflows move from insight to action  
  • Reflects the types of solutions organizations are building today, not just exploring  

3. AI Governance and Trusted Data Foundations at Snowflake Summit

Session: What’s New: Innovations in Data and AI Governance (WN210B)
Speaker: Snowflake 
Date & Time: Tuesday, June 2 | 3:30–4:15 PM PDT 

As organizations expand their use of AI, governance becomes more tightly connected to day-to-day development and operations. This session focuses on how Snowflake is evolving its governance capabilities to support that shift. 

Updates to Horizon Catalog, improvements to semantic alignment, and expanded interoperability through open standards all point toward a more unified approach to managing data and AI assets. Capabilities like automated classification, lineage, and data quality monitoring are increasingly central to how organizations maintain trust as they scale. 

Why we’re interested: 

  • Connects governance directly to how AI is built and deployed  
  • Highlights tools that support consistency across complex environments  
  • Reinforces the importance of strong data foundations  

Snowflake Summit Takeaways for Higher Education and Government Leaders

Across these sessions, a consistent pattern emerges: organizations are moving from isolated AI experiments to integrated, operational solutions that are governed, scalable, and tied to real outcomes. 

That’s where Avaap focuses. As a consulting partner for higher education and government organizations, we help teams apply these patterns in ways that align with their data, systems, and institutional priorities. If you’ll be attending Snowflake Summit, we invite you to schedule time to connect with the Avaap Data, Analytics, and AI team using our meeting request form and continue the conversation onsite.

Schedule Time to Connect

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Workday is a powerful system of record for people, money, and planning. But as organizations mature in their Workday journey, a common question emerges: how do you move beyond operational reporting to enterprise-wide insight without compromising performance, security, or governance? 

For many Workday customers, the answer is Snowflake. 

Snowflake serves as the analytics and AI layer downstream of Workday, allowing Workday data to scale beyond transactional reporting and become enterprise data.

This architecture preserves Workday’s role as the system of record while enabling the depth, history, and flexibility required for enterprise analytics and AI readiness. 

Together, Workday and Snowflake create a modern data foundation, one that supports executive decision-making without placing additional strain on operational systems. 

How Snowflake Extends Workday Analytics Beyond Operational Reporting 

Workday provides a unified operational foundation across HR, Finance, and Planning. Once that foundation is in place, organizations begin looking for broader visibility—insight that spans domains, extends across years of data, and supports strategic planning. 

Snowflake is where that expansion happens. 

By extending Workday data into Snowflake, organizations unlock enterprise-scale analytics while maintaining performance and governance. Workday continues to power day-to-day operations. Snowflake becomes the platform for insight, intelligence, and long-term analysis. 

From Workday System of Record to Enterprise Analytics Platform 

Workday and Snowflake are purpose-built for different, but complementary, roles. Workday excels at operational execution and transactional reporting. Snowflake is designed for analytics at scale, cross-domain insight, and advanced workloads. Together, they enable a clear separation of responsibilities that protect core systems while expanding analytic capability. 

For Workday customers, this approach supports: 

  • Enterprise-wide analytics without impacting Workday performance 
  • Cross-domain insight by combining Workday data with other enterprise sources 
  • A governed foundation for advanced analytics and AI initiatives 

The result is a scalable, future-ready architecture without disruption. 

Enabling Enterprise and Executive Analytics with Workday and Snowflake 

Using Workday and Snowflake together allows organizations to answer strategic questions that operational reporting alone cannot support. 

With Snowflake downstream of Workday, leaders gain access to historical, longitudinal, and cross-functional insights that support planning, performance management, and enterprise decision-making—while Workday remains focused on what it does best. 

Why Workday Organizations Are Adopting Snowflake for AI Readiness 

Workday customers are moving now as several forces converge: 

  • Executives expect insights that cut across people, money, and operations 
  • AI initiatives require scale, openness, and historical depth 
  • Years of Workday data are compounding in strategic value 

Snowflake meets these demands while allowing Workday to remain in the trusted system of record. 

Download the Full Whitepaper 

This blog provides a high-level view of why Snowflake has become the preferred analytics and AI architecture for Workday customers. 

The full whitepaper goes deeper into: 

  • Architecture patterns and governance considerations 
  • Real-world executive use cases 
Download the full whitepaper