COURSE OVERVIEW

 This practical and highly-interactive course includes real-life case studies where participants will be engaged in a series of interactive small groups and class workshops. 

 

This course is designed to provide participants with a detailed and up-to-date overview of Data Analysis of Environment, Health, Safety and Security Systems (EHSS). It covers the importance of data-driven decision-making in EHSS including the key challenges in EHSS data collection and analysis; the regulatory and compliance requirements for EHSS data and EHSS reporting frameworks; the data collection in EHSS systems, data cleaning and preparation for EHSS analysis; the data analysis (EDA) in EHSS systems and key performance indicators (KPIs) in EHSS; and the EHSS data management platforms, spreadsheets and databases for EHSS data storage. 

 

Further, the course will also discuss the integration of data from multiple EHSS sources; the data governance and security considerations; the types of environmental data and regulatory requirements for environmental data reporting; the data analysis of air quality and emissions, water quality and wastewater data analysis, waste management and hazardous materials data analysis; and the sustainability and carbon footprint analysis and environmental risk assessment using data analytics. 

During this interactive course, participants will learn the sustainability and carbon footprint analysis and environmental risk assessment using data analytics; the ergonomic and human factors data analysis, behavioral safety and leading indicators analysis and predictive analytics for safety performance improvement; the security threat identification and data analysis, surveillance data and physical security analytics and cybersecurity and IT security data analysis; the emergency preparedness and crisis data management, insider threats and fraud detection using data analytics and integrating EHSS risk management and decision support systems; the machine learning and AI in EHSS analytics, big data and EHSS analytics, data visualization and dashboarding in EHSS and EHSS data-driven decision making; the emerging technologies in EHSS analytics and predictive and prescriptive analytics in EHSS; and the blockchain for EHSS data security and transparency and preparing for the future of EHSS analytics.