How to Detect Lack of Data Integrity 2016

Topics

• Case studies illustrating types and sources of data integrity issues
• What is data integrity; what does it look like
• Computer, analytical and statistical methods for evaluating data integrity and quality
• Procedures for assessing data pedigree, integrity and quality
• Guiding principles, tips and traps for the effective data integrity assessment
• Limitations of observational data

Who should Attend

Senior attendees involved or interested in:

• Quality Assurance Team Members
• Senior management
• Compliance Auditors
• Quality Control Team Members
• Supply Chain and Logistics Managers
• Process Development Team Members
• Engineering Staff
• Regulatory Affairs Team Members
• IT Management and Staff working in regulated areas