Break through the noise and delve into what data analytics means, and how they can be applied in the real world. Don’t miss the opportunity to learn the essentials during this level-setting introductory session, as we lay the groundwork for the main conference discussions.

Part I: Terminology and Definitions

• What is and isn’t data analytics
• The difference between predictive modeling and predictive analytics, and how supervised learning and unsupervised learning factor in
• Delineating between Machine Learning, Artificial Intelligence and predictive analytics
• How data mining has different meanings in different contexts, and when it is applied to text mining

Part II: Applications and Practices

• Establishing what you want to accomplish from developing your program-and what is achievable based on your organization, industry and budget
• Identifying your data sources and resources
• Using qualitative versus quantitative data
• Monitoring and reporting essentials

Part III: Predicting

• Identifying red flags and trends
• When does analytics jump from identifying to predicting bribery and corruption?