Keynote: From Raw Data to Running Predictions — Accelerate Your ML Workflow from Weeks to Minutes

What if the journey from raw data to machine learning predictions could be dramatically accelerated? For enterprise data science teams, reducing the time spent preparing data, building models, and deploying predictions is essential to delivering AI-driven business value. In this keynote, "Keynote: From Raw Data to Running Predictions — Accelerate Your ML Workflow from Weeks to Minutes," from COLLIDE Data + AI Conference 2026, Shan Kulandaivel, Group Product Manager @ Google Cloud, explores one of the most important challenges in enterprise machine learning: simplifying and accelerating the end-to-end ML workflow. Traditional machine learning development often involves multiple stages, including data preparation, feature engineering, model training, evaluation, and deployment. Coordinating these processes across tools, infrastructure, and teams can introduce complexity and slow down the delivery of production-ready AI applications. As organizations invest in cloud-based AI platforms and modern data infrastructure, streamlining the machine learning lifecycle is becoming increasingly important. This keynote offers an opportunity to consider how more integrated ML workflows can help data scientists and ML engineers spend less time managing infrastructure and more time developing, testing, and operationalizing predictive models. 🎯 Key Topics to Explore: Accelerating ML Workflows: Approaches to reducing the complexity and time required to move from raw data to running predictions. End-to-End Machine Learning: The relationship between data preparation, model development, evaluation, and deployment in modern ML pipelines. Cloud-Based AI Development: How cloud infrastructure and integrated machine learning platforms can support efficient model development. MLOps and Workflow Automation: The importance of repeatable processes, automation, and operational consistency in enterprise machine learning. Scaling Predictive AI: Key considerations for building reliable, efficient, and production-ready machine learning applications. 🎤 Featured Keynote Speaker Shan Kulandaivel Group Product Manager | Google Cloud About COLLIDE Data + AI Conference 2026 Organized by Data Science Connect, COLLIDE Data + AI Conference 2026 took place on October 1, 2026, at the Sandy Springs Performing Arts Center in Atlanta, Georgia. The conference brought together enterprise decision-makers, data and AI executives, technology practitioners, and leading AI solution providers to explore the evolving AI landscape, scale AI responsibly, and exchange practical insights with industry peers. Session Presented By: Google Cloud Learn more about COLLIDE: https://datasciconnect.com/events/collide/ ▶️ Watch More from COLLIDE 2026 Watch the full keynote to explore the opportunities and considerations involved in accelerating machine learning workflows, from raw data to running predictions. Subscribe to the Data Science Connect YouTube channel for more executive keynotes, technical presentations, and industry discussions from COLLIDE Data + AI Conference 2026 covering machine learning, data science, MLOps, cloud AI, and enterprise AI transformation.