About
Experience & Education
Volunteer Experience
Publications
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Insights (Possible Mobile Corporate Blog)
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See publicationA brief article regarding the importance of the role of Business Analyst in large projects.
Honors & Awards
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Microsoft Patent Cube
Microsoft
Systems And Methods For Creating Autonomous Agents For Testing Interactive Software Applications. This product is now branded as "QA Copilot".
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University of Alabama Academic Honors Scolarship
University of Alabama
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University of Alabama College of Engineering Scholarship
University of Alabama
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University of Alabama Honors Program
University of Alabama
Organizations
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USA Cycling
Athlete, Official
- Present -
American Mensa
Member
- Present
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Veronika Durgin
I’ve been told I have some Better Off Dead–level opinions. You might be better off dashboard-less. Better off debt-less. Definitely not better off pretending AI can resurrect a shaky foundation. Sometimes data strategy feels like: "And: new tool" "Followed by BI dashboard" "And to drink: Ta-da! AI" It’s confidently delivered. But are we actually serving value? I’ll be hanging out with the Super Data Brothers (Ryan and Eric) on March 5th talking about what it really takes to deliver outcomes. If none of this makes sense, just join the podcast... and maybe watch the 80s classic Better Off Dead. No paperboys were harmed in the making of these opinions. And no one owes anyone two dollars.
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Robin Beura
When a Data Challenge Turns Into a Lesson on How to Think Like a Builder 🚀📊 I recently wrapped up the Capital One Data Challenge — a really thoughtful exercise that tested more than just technical skills. It pushed me to think like a builder, not just an analyst. A few key takeaways that stayed with me 👇 1️⃣ Reproducibility matters more than perfection. I designed my solution using modular, reusable functions — something that could run again tomorrow with new data. It reminded me that scalable analytics comes from clean engineering, not clever shortcuts. 2️⃣ Data quality is the first real model. Before a single chart, I built structured checks for missing values, schema drift, and outliers. I learned how every downstream metric depends on invisible upstream hygiene. 3️⃣ Translate business logic into data logic. Every rule — from costs to operational assumptions — had to be expressed through code. It was a real exercise in connecting business reasoning with analytical precision. 4️⃣ Visualization is storytelling, not decoration. I focused on clarity — visuals that show trade-offs, breakeven points, and trends executives can actually act on. 5️⃣ What I did differently: I built scenario modeling directly into the workflow — parameterizing key drivers like delay cost, fuel rate, and occupancy. That turned static results into a living decision tool. It’s the kind of flexibility real teams need when business conditions shift. Overall, the challenge was a reminder that analytics isn’t just about accuracy — it’s about building tools that think, flex, and explain. If you’ve worked on similar challenges or love talking about how analytics can drive better decisions, I’d love to connect and exchange ideas. #DataScience #Analytics #DecisionScience #BusinessIntelligence #DataProducts #CapitalOne
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Pupsic
Snowflake’s dynamic AI model routing cuts enterprise AI costs by automating task assignment to the most efficient models, reducing expenses by up to three times. This approach balances quality, governance, and security within Snowflake’s platform, helping enterprises manage AI at scale more effectively.
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