This talk will present:

1. how graphs can be used to virtually integrate data from different, heterogeneous sources and;
2. how semantics can be added to make data smarter and enhance search.

We will present two case studies focused in finance and healthcare.

First, we will present how a large Multi-level Marketing organization, after multiple failed Enterprise Data Warehouse efforts, was able to make sense of their inscrutable order-management system by using semantic and data virtualization technologies. The time and cost to generate financial reports were dramatically reduced and more accurate reports resulted.

Second, we will present a patient stratification case study from the Ohio State University Wexner Medical Center. Traditional Enterprise Data Warehouse solutions did not satisfy the need due to cost and data privacy. By using semantic and data virtualization technologies, the medical center was able to identify 30% more patients in need of Left Ventricular Assist Devices (LVAD).

The attendees will learn about:

• Methodology to create Knowledge Graphs in conjunction with mappings
• Architectural decisions on virtualization (NoETL) versus materialization (ETL)
• Intuitive ways to model financial and patient health information
• Searching financial and patient information which matches desired criteria