Big Data in Demand Planning equips participants with essential skills to leverage data analytics in optimizing inventory management and forecasting demand. This course emphasizes practical application through project-based learning, enabling participants to engage directly with real-world data sets and scenarios. By focusing on the intersection of big data and demand planning, attendees will learn to enhance decision-making processes and improve operational efficiency within retail and logistics sectors.
The curriculum is structured to provide a comprehensive understanding of demand forecasting methodologies, data analysis techniques, and the implementation of predictive models. Participants will explore advanced analytical tools and software, culminating in a final project that requires the development of a demand forecasting model using big data principles. This hands-on approach not only solidifies theoretical knowledge but also prepares participants to publish their findings in Cademix Magazine, fostering a culture of knowledge sharing and professional development.
Introduction to Big Data Concepts in Demand Planning
Data Sources and Data Collection Techniques
Statistical Methods for Demand Forecasting
Time Series Analysis and Forecasting Models
Machine Learning Applications in Demand Planning
Inventory Optimization Techniques
Case Studies on Successful Demand Planning Strategies
Tools and Software for Big Data Analysis
Developing Predictive Models for Demand Forecasting
Final Project: Creating a Big Data Demand Forecasting Model