Olena Kulish
Digital Analytics & Data Intelligence Specialist at NCOA |Power BI, Microsoft Fabric, AI-Ready Analytics
Washington, District of Columbia, United States
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Lena is a Digital Analytics Specialist working at the intersection of analytics, governance, and AI readiness in the public sector. She holds a Master’s degree in Marketing Analytics from the University of South Florida and has played a key role in delivering analytics solutions for more than 20 mission-driven organizations across the DMV and nationwide, helping transform fragmented data into actionable insights that support large-scale impact.
Currently, she leads analytics strategy for a national nonprofit, focusing on building AI-ready analytics environments through improved data architecture, governance, and adoption of analytics solutions.
Lena is also passionate about mentorship and teaching. She has supported early-career professionals in securing internships and their first roles, and has served as a guest facilitator at the University of South Florida, leading discussions on marketing analytics, customer behavior, and machine learning applications.
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Before They Go: Building Churn Prediction Models in Microsoft Fabric
Every organization has users, customers, or supporters who begin to disengage before they leave — and most teams don't spot the warning signs early enough. Churn prediction models can change that.
In this session, I'll walk through how to build an end-to-end churn prediction workflow in Microsoft Fabric, using a real-world nonprofit example to show how the same approach applies across fundraising, membership, and customer success. Attendees will leave with a practical understanding of how Fabric supports churn modeling: from data preparation to prediction to retention-focused insights.
Why Power BI Adoption Fails — and How to Fix It with Governance, UX, and AI-Ready Usage Data
In this session, we explore why many Power BI and Microsoft Fabric initiatives struggle with low dashboard adoption, inconsistent usage, and limited impact — and why these challenges are rarely technical.
Drawing from my experience leading analytics in a national nonprofit in the public sector, I will share a practical framework for improving adoption using engagement metrics, behavioral insights, and governance models.
We will cover how to measure true adoption, identify why dashboards fail, and implement feedback loops that drive continuous improvement across Power BI and Fabric environments.
A key focus is how adoption and governance enable AI-ready analytics — using structured usage data, trusted definitions, and data discoverability to support reliable insights and scalable decision-making.
You will learn how to diagnose adoption issues, design solutions users actually engage with, and build a foundation for immediate impact and long-term AI readiness.
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