Graph analytics Applications in new AI Era 

Graphs are amazing. You can model data in a new way that lets you understand relationships, discover patterns and anomalies, and classify and analyze connected data. This lets you answer questions such as who the most important customers and suppliers are, where the critical points in a supply chain are, or which financial transactions may be fraudulent.

In this presentation, speakers will talk about two real project implementations and how Graph analytics techniques are used to create additional value on traditional analytics methods.  In Financial services, they will discuss how money transfer data is used to understand cyclic money transfers to detect financial fraud, understand organized money laundry activites and find the patterns for suspicious fundings. In Public Safety domain, they will share experiences and very interesting results about Crime Investigation using connected network graph approaches. After this session, you will be familiar with real life challenges of graph implementations, expected outcomes, business benefits and how you can start implementing network graphs for your own business problem.


Hatice Kubra Canel, EMEA Data Science Lead @ Oracle Deutschland BV & Co KG

Hatice Kubra Canel has MSc. in Industrial Engineering, and advanced career in Big Data, Analytics, Data Science and Cloud area. Experienced in AI, ML, Big Data, BI and cloud solutions and worked in well-known global companies since 2010. Currently, she is the EMEA Data Science Lead in Oracle.

Ilhan Ercan, Co-founder @ Datateam

Ilhan Ercan is co-founder of Datateam and more than 20+ years experience in data related projects. He has advanced level experience on Oracle Databases & Analytics software. After establishing Datateam, from day one he and his team have been focused on Graph based Data Analytics.