Data Intelligence and Analytics Company
The client provides decision science and data management solutions that empower companies to identify the insights needed to make timely and accurate business decisions. It is based out of New York, US
Developing an accurate predictive analysis and sales forecast model for a specific retail store and product during promotional events. The challenge involves leveraging historical data, customer behavior, and promotional strategies to optimize sales projections, enabling the store to efficiently plan inventory, marketing, and resources to meet demand and maximize profits.
Implementing an efficient data flow and processing pipeline with a powerful ML engine will revolutionize the retail store's sales forecasting during promotions. The AI pipeline's well-architected design ensures top-notch quality, security, and cost optimization. The seamless integration of various components will enable the generation of accurate baseline and forecasted sales, empowering the management with clear financial reports accessible through a user-friendly UI console. This transformative solution will enhance decision-making, streamline inventory management, and maximize profitability, ultimately positioning the retail store for sustainable growth and competitive advantage.
Zymr's cutting-edge expertise in AI-native applications and platform engineering sevices, bolstered by comprehensive lifecycle management and MLOps capabilities, delivered exceptional value to our esteemed clients. Leveraging Azure's robust infrastructure, we crafted an advanced AI solution infused with time series forecasting, data classification, and other ML functionalities, enabling precise predictions of baseline and forecasted sales. Our data science team collaborated closely with the client, comprehending their business goals deeply, and crafting ML models in consultation with key stakeholders. The MLOps team orchestrated a robust data ingestion pipeline, housing raw, feature-engineered, and golden datasets in a secure SQL database. By utilizing classification algorithms, the data was intelligently categorized based on sales volume (e.g., fast-moving, seasonal), while time series algorithms like ARIMA empowered us to build accurate forecasting models. The solution drives improved decision-making, enhanced inventory management, and boosts overall business performance for our valued clients.
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