Dr. Santikary is an accomplished technology executive with over 20 years of experience in building distributed systems, platforms and applications using techniques of modern data architecture, distributed computing and cloud computing. He has worked in the clinical research, pharmaceutical, e-commerce, banking, financial and energy sectors, driving global data and platform strategy and overseeing execution. In his current role as Vice President and Chief Data Officer at ERT, a global data and technology company supporting clinical trials for small, medium and large pharmaceutical and bio technology companies, Dr. Santikary is leading the strategy and execution of ERT’s global data architecture, data integration, business intelligence, advanced analytics, data governance, master data management and data science.
Before joining ERT, Dr. Santikary held several technology executive roles across a variety of industries, including serving as Head of Data Engineering and Director of Engineering at eBay, VP of Engineering at Zeta Global, Chief Architect and Technologist at Sunovion Pharmaceuticals, Director of Data Science and Engineering at EnerNOC, Chief Data Architect at PNC Financial, Chief Architect at S1 corporation and Research Scientist at The University of Michigan, Ann Arbor.
An industry thought leader and a data evangelist, Dr. Santikary is a frequent speaker at software engineering conferences, summits and symposiums on modern data architecture and emerging computer science-related topics including cloud computing, artificial intelligence and machine learning.
Dr. Santikary earned his PhD in Computer Simulation from Indian Institute of Science (IISc) in Bangalore, India, and post-doctoral research at The University of Michigan. He is the recipient of multiple national and international research fellowships, including a doctoral fellowship from Indian Institute of Science, Bangalore, a post-doctoral fellowship from The University of Michigan, Ann Arbor; and an advanced research fellowship from The Council of Scientific and Industrial Research (CSIR), Government of India.
Modern data platform at scale – best practices on microservices architecture, lambda architecture and serverless computing
Clinical trials are fraught with missteps and data quality issues that often create costly delays in bringing life-saving drugs and diagnoses to the market. Often times, data quality issues and data integration challenges cause clinical trials to fail. Today’s complex clinical studies, which are also distributed around the globe, generate vast amounts of data from disparate sources, mobile heath devices, Internet of Things (IOTs), systems, vendors and clinical endpoints. Not only is the clinical data voluminous, it’s often comes at tremendous velocity commingled with data variety including a combination of structured, unstructured and binary data format. On top, these disparate systems don’t talk to each other in a standard manner, creating data silos and inhibiting real time integrated clinical trial information for real time decision making, risk analysis and regulatory compliance monitoring. This presentation will be focusing on the architecture of a modern, cloud-based real time data integration and analytics platform that ingests any type of clinical data (structured, unstructured, binary, lab values, etc.) at scale from any data sources. The presentation will focus on laying out the architectural building blocks of this modern data platform including explaining our “serverless” data pipeline, cloud architecture and deployment, continuous integration and deployment pipeline, platform scalability, data governance and master data management.