Mihir Dhakan

From Data Pipelines to Intelligence Pipelines: Rethinking Data Architecture

Abstract:

Most organizations today are rich in data but poor in decisions. Over the years, data pipelines have become faster, bigger, and more complex—yet forecasting and analytics outcomes often remain inconsistent and hard to trust.
This keynote tells the story of why traditional data pipelines are no longer enough. It explores how data architecture must evolve into intelligence pipeline systems designed not just to move data, but to deliver insights, forecasts, and decisions that people actually use. Drawing from real-world industry experience, the talk walks through how analytics and demand forecasting break down when architecture is designed without the end decision in mind.
By rethinking pipelines around intelligence, trust, and adoption, organizations can move from reporting the past to shaping the future. The session offers practical architectural ideas for building data platforms that support smart computing in the real world.

Profile:

Mihir Dhakan is a Data Engineering Manager and data architecture leader with over ten years of global experience spanning the United States, Canada, Singapore, Australia, Malaysia, and India. He specializes in designing and scaling cloud-native data platforms that power analytics, forecasting, and intelligent decision-making in complex enterprise environments.

Currently at Upshop, Mihir leads the development of unified data frameworks and predictive data systems that enable smarter planning and operational decisions across retail organizations. His work covers end-to-end data architecture, pipeline engineering, governance, and the integration of advanced analytics and GenAI capabilities using modern Azure-based platforms.
Previously, Mihir held senior and principal data engineering roles at organizations including OCBC Bank, Standard Chartered, and Tata Consultancy Services, delivering high-impact data solutions across banking, finance, SaaS, insurance, and media domains. Working across multiple geographies has shaped his practical approach to data architecture—one that balances scalability, compliance, and real-world usability.

Known for building and mentoring globally distributed teams, Mihir bridges technical depth with strong stakeholder collaboration. His professional interests include intelligent data pipelines, demand forecasting systems, and transforming data platforms into engines for actionable business insight.