Hyderabad: IIIT Hyderabad is hosting the 10th international conference on Big Data Analytics at its campus in Gachibowli. It is a four-day conference that kicked off yesterday and will conclude on 22nd December.
The conference is an international forum for researchers and industry practitioners to share their original research results, practical experiences and thoughts on big data from different perspectives including storage models, data access, computing paradigms, analytics, information sharing and privacy, redesigning mining algorithms, open issues, and future research trends.
It includes 4 workshops (on Data Challenges in Assessing (Urban & Regional) Air Quality, Big Data Analytics using HPCC Systems, Data Science for Justice Delivery in India and workshop on Universal Acceptance and Email Address Internationalization)
It also includes 4 keynote talks by Y Narahari, Indian Institute of Science, Bangalore; Sanjay Madria, Missouri University of Science and Technology, USA; Raj Sharman, University at Buffalo and Philippe Fournier-Viger, Shenzhen University, China
It will have 4 tutorials (on Malware Analysis and Detection, Neuro-Symbolic Techniques for XAI and Logical Reasoning, Federated Learning in the Real-World: From Theory to Practice and Self-Supervised Learning to Process Labeled and Unlabeled Medical Image Data
A panel discussion on Data Science for sustainable development goals with Masaru Kitsuregawa (The University of Tokyo), Jaideep Srivastava (University of Minnesota), Longbing Cao (University of Technology Sydney), Santanu Chaudhury (IIT Jodhpur) and Yun Sing Koh (University of Auckland). The discussion was moderated by Philippe Fournier-Viger, Shenzhen University and P.Krishna Reddy, IIIT Hyderabad will be held.
Two invited talks by Sridhar Viswanathan, Bank of America and S Bapi Raju, IIIT Hyderabad; 3 industry talks are also part of the meet. 14 research papers will be presented during the meeting.
In recent times data generation at the scale of terabytes, petabytes and exabytes have become commonplace in many scientific and commercial domains. Streaming data, social media content, electronic medical records, astronomy surveys, genomic and proteomic studies and similar areas generate data at a scale that is becoming increasingly difficult to manage using traditional database technologies. Big Data is an umbrella term used for such massive collections of data.
Besides volume, analytics has to face challenges like heterogeneity, timeliness, and complexity, velocity and privacy issues. The other challenge is to fuse data sources – of same type or multi-modal and perform joint analytics on the integrated data. The scale of such data poses significant challenges for analytics, going beyond what can be supported by conventional data, storage and retrieval models. The International Conference on Big Data Analytics (BDA) is set in this backdrop.