Modern Data Architectures for Scalable Analytics

11:00 AM - 12:00 PM
Arjun Shankar, Computational Data Analytics Group, ORNL Computer Sciences and Engineering Division
Urban Dynamics Institute Seminar
Joint Institute for Computational Sciences (Building 5100), Auditorium (Room 128)
Email: Beata E. Taylor


Mallikarjun (Arjun) Shankar will discuss the emergence of modern data architectures that support large-scale analytics. The recent data science buzz owes its origins to the proliferation of sensor data and associated communications networks, storage systems improvements, and the improved ability to network and to harness computing. These drivers of data growth and the advances in data processing have brought about remarkable engineering innovations over the last decade. Although these modern data infrastructures enable us to process large data volumes cheaply, they have also given rise to increased competition between established approaches and what may appear to be new data-processing paradigms. This talk will highlight the pros and cons of these new data architectures in the context of the kind of analytics they support and give examples from two nationally significant mission areas: monitoring wide-area electric grid stability and integrating large-scale data sets for healthcare fraud analytics.

About the Speaker:
Arjun Shankar is a senior research scientist in the Computational Data Analytics Group within the ORNL Computer Sciences and Engineering Division. His research interests are bridging advances in computer science with interdisciplinary domain problems in sensor networks, energy systems, and healthcare information systems, which increasingly rely on information infrastructure and large-scale data processing. He received his master's degree and doctorate in computer science from the University of Illinois, Urbana-Champaign and his bachelor of technology degree from the Indian Institute of Technology. He is a member of the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers Computer Society.


We're always happy to get feedback from our users. Please use the Comments form to send us your comments, questions, and observations.