Raghavender Puchhakayala Puchhakayala
Senior Member IEEE / JPMorgan Chase
Dallas, Texas, United States
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I am a seasoned professional with over a decade of experience in Data Warehousing, Business Intelligence (BI), and Analytics across industries such as Banking, Healthcare, and Retail. Currently, I work as an Analytics Solutions Associate Sr. at JP Morgan Chase, where I have led BI system migrations, executive dashboard development, and data optimization initiatives. My expertise spans Tableau, Business Objects, Cognos, and PL/SQL, with a strong focus on data governance and AI-driven analytics to enhance decision-making and operational efficiency.
I hold a Master’s degree in Computer Science from the University of Missouri-Kansas City and have earned certifications in Tableau, Microsoft Azure, AWS, and Alteryx. As an active IEEE member and peer reviewer, I am committed to advancing technology by contributing to technical reports, research publications, and mentoring. I am passionate about driving BI transformation projects that enable data-driven strategies, regulatory compliance, and business innovation.
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Agentic AI and the Future of Financial Decision Making
Join us online for an exciting dive into how agentic AI is reshaping the way we make financial decisions. Discover the latest trends, innovative tools, and the potential impact on markets and personal finance. Whether you're a tech enthusiast or a finance pro, this event offers fresh insights and lively discussions. Don’t miss out on exploring the future of finance with cutting-edge AI!
AI-Driven Financial Analytics: Industry Perspectives on Data-Centric Decision Making
Financial institutions today operate in an environment defined by unprecedented data volumes, rapid market volatility, and increasing regulatory complexity. Traditional analytics approaches, while foundational, are no longer sufficient to meet the demands of real-time, high-stakes financial decision-making. This keynote explores how AI-driven financial analytics is reshaping industry practices by enabling data-centric, scalable, and intelligent decision systems.
Drawing from industry experience, the talk examines how organizations are operationalizing artificial intelligence across key financial functions, including risk assessment, fraud detection, forecasting, customer analytics, and regulatory compliance. The session highlights practical applications of machine learning, deep learning, and advanced analytics, focusing on how these technologies convert raw financial data into actionable intelligence.
Beyond technical models, the keynote emphasizes critical industry challenges, such as data quality, model interpretability, bias mitigation, governance, and regulatory alignment. Special attention is given to explainable and responsible AI, illustrating how transparency and trust are becoming central requirements for enterprise adoption.
The presentation also bridges research and practice, identifying gaps where academic innovation can better align with real-world financial constraints. By sharing lessons learned from deploying AI at scale, this keynote provides a pragmatic view of what works, what fails, and what lies ahead.
Attendees will gain insights into how AI-driven analytics is not merely an optimization tool, but a strategic capability redefining financial decision-making. The session concludes with a forward-looking discussion on emerging trends, including automation, real-time analytics, and the evolving role of advanced computing in future-ready financial systems.
Unlocking Business Insights: Harnessing BI Tools and AI for Strategic Decision-Making
In today's data-driven world, the ability to extract actionable insights from complex data landscapes is crucial for business success. This session will explore how cutting-edge Business Intelligence (BI) tools and AI technologies can be leveraged to enhance decision-making processes across industries such as banking, healthcare, and retail. Drawing from over a decade of experience in designing executive dashboards and optimizing data models, I will share practical strategies for integrating BI systems with AI-driven analytics to unlock valuable business insights. Attendees will gain insights into the full SDLC of BI systems, from analysis and design to implementation and migration, ensuring seamless transitions and improved data accessibility. Real-world case studies will demonstrate the transformative power of BI and AI in driving innovation and efficiency.
Key Takeaways:
How to integrate BI tools with AI technologies for enhanced decision-making
Real-world examples of BI and AI impact across banking, healthcare, and retail
Strategies for optimizing data models and reporting solutions
Overcoming challenges in data integration and migration
Bridging Legacy BI with Modern Cloud Data Stacks: A Practical Guide to Migration and Insight Deliver
In this session, we’ll walk through how organizations can modernize their BI and reporting infrastructure by transitioning from legacy tools like Business Objects to cloud and open-source platforms like JasperReports, Tableau Public, and Python analytics libraries. I’ll demonstrate how to design scalable, interactive dashboards, build efficient data models, and create cloud-integrated pipelines using AWS and Azure services.
We’ll explore how to:
Migrate BI assets to modern tools without disrupting users
Design impactful dashboards and reports for diverse stakeholders
Integrate Python for data analysis and automated reporting
Leverage Azure and AWS for storage, orchestration, and scalability
Maintain governance and reliability during transformation
This session is ideal for beginners to intermediate users interested in building a modern data stack and delivering actionable insights through BI modernization.
Unlocking the Power of Quantum Computing: From Theory to Real-World Applications
Explore the transformative potential of quantum computing! From cutting-edge research to open-source tools, learn how quantum algorithms are solving problems beyond classical computing’s reach. Join us to demystify the future of computing!
Transforming Quantitative Data Analytics with AI: From Insights to Actionable Decisions
Discover how AI is revolutionizing quantitative data analytics! Learn how machine learning models are unlocking deeper insights, improving accuracy, and driving smarter decisions in finance, healthcare, and beyond.
Raghavender Puchhakayala Puchhakayala
Senior Member IEEE / JPMorgan Chase
Dallas, Texas, United States
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