Semantic Analytics

Analytics are connecting companies with their customers – with better understanding of their interests and the products/services that they need. To date, semantic technology has been addressing data management challenges associated with analytics that must be resolved before analytics begin. Now, semantic and cognitive techniques are augmenting conventional data-driven analytics to provide more accurate results as well as new insights from the data.

This presentation will describe knowledge-based reasoning techniques to expand and accelerate insight delivery, including:

Data discovery to find unrealized patterns and trends
Clustering through semantic tagging
Identifying and predicting behavior changes
Graph Pattern Matching to find similar customers
Analyzing data in the long tail
Comprehensive risk analysis from disparate distributed data

Thomas Kelly is a Practice Director in Cognizant's Enterprise Information Management (EIM) Practice and heads its Semantic Technology Center of Excellence. He has 20-plus years of technology consulting experience in leading data warehousing, business intelligence and big data projects, focused primarily on the banking/financial services, life sciences and healthcare industries.

Successful semantic graph analytics scientist applying his talents to developing customers’ product strategies and architectures for analytics and decision support. Keen possesses a deep understanding of graph analytics, predictive modeling, unstructured data, categorization, text mining, natural language processing, data mining algorithms, neural networks, and Artificial Intelligence. He has used his expertise in these areas to provide thought leadership and develop applications and evaluations in multiple domains including intelligence/security informatics, business intelligence, cyber security, financial analysis, corporate governance, retail and energy.