Big Data Analytics for Supply Chain Optimization

Overview of supply chain management

Introduction to big data analytics

Importance of big data analytics in supply chain optimization

Methods for collecting supply chain data

Data integration techniques for disparate data sources

Data quality assessment and assurance

Overview of big data storage technologies (e.g., Hadoop, NoSQL databases)

Data warehousing and data lakes for supply chain data

Data governance and security considerations

Descriptive, predictive, and prescriptive analytics

Data visualization techniques for supply chain insights

Predictive modeling for demand forecasting

Role of IoT sensors and devices in supply chain data collection

Real-time data processing and analysis techniques

Applications of real-time analytics in supply chain monitoring and decision-making

Introduction to machine learning algorithms (e.g., clustering, classification, regression)

Applications of machine learning in supply chain optimization

Deep learning techniques for anomaly detection and pattern recognition

Risk assessment and mitigation strategies in supply chain management

Predictive analytics for identifying potential disruptions

Resilience planning and scenario analysis using big data