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Explore a 14-minute conference talk demonstrating how retail and consumer packaged goods companies can overcome traditional forecasting challenges using Workcloud Modeling Studio, a low-code/no-code machine learning platform. Discover how this innovative tool addresses the growing pressure on retail and CPG companies to improve demand forecasting, optimize pricing, and manage inventory more effectively, while reducing deployment time from months to hours. Learn about the limitations of traditional forecasting approaches that require extensive engineering support and lengthy implementation timelines. Follow a comprehensive walkthrough of a real-world demand forecasting use case for a retailer using Zebra's Modeling Studio, presented by Moez Ali, AI Product Director at Zebra Technologies. Understand the step-by-step process of building, training, and deploying a complete ML forecasting pipeline without the need to develop solutions from scratch. Gain insights into how low-code/no-code platforms can significantly improve forecasting accuracy while accelerating time-to-value for data scientists working in retail and CPG environments. See practical demonstrations of the platform's capabilities and learn how it streamlines the machine learning workflow for business-critical forecasting applications.
