Recently, David Bader visited India to give a keynote talk at IEEE International Conference on Machine Learning and Data Science at Bennett University, Greater Noida. David A. Bader is Professor and Chair of the School of Computational Science and Engineering, College of Computing, at Georgia Institute of Technology. He is a fellow of the IEEE and AAAS and served on the White House's National Strategic Computing Initiative (NSCI) panel. He was in conversation with Prof. Deepak Garg, Chair, of Computer Science Engineering at Bennett University. Question: Big data and data analytics have made a huge impact on businesses in 2017, with trends like artificial intelligence and cloud services being used for their advantage.

While data analytics, IoT, and AI are fast becoming normalized terms in the business world, it is generally perceived as reserved for the more adventurous companies, and not for the likes of conservative industries such as pharmaceuticals. This is certainly not the case anymore according to AstraZeneca's Steve Woodward who is leading the charge of data analytics within the pharma giant. Data is one of the areas which is defining the future of the business, mainly because of the vast amount of data which the company has. And this is only increasing at a faster and faster rate. For Woodward, a DevOps approach was crucial to increase the pace of development and production. The team is currently processing around 2,500 queries a minute, meaning the implementation of containers was a must.

Some chronic conditions, such as the autoimmune disease scleroderma, are especially difficult to treat because patients exhibit highly variable symptoms, complications and treatment responses. The process of finding an effective treatment for an individual can be frustrating for doctors, and painful and expensive for patients. With support from the National Science Foundation (NSF), computer scientist and professor Suchi Saria, with Dr. Fredrick Wigley and an interdisciplinary team of experts at Johns Hopkins University, is leading a groundbreaking effort using Big Data to ease some of that pain for scleroderma patients. The team s research is in machine learning, a subfield of computer science and statistics that allows machines to learn from data. The team designs statistical algorithms that enable computers to analyze large volumes of medical records and identify subgroups of patients with similar patterns of disease progression.