Abstract: Abstract: We live in a data-driven world as everyone around has been telling us for some time. Everything is generating data, in volumes and at high rates, from the sensors embedded in our physical spaces to the large number of machines in data centers which are being monitored for a wide variety of metrics. The question that we pose is: Can all this data be used for improving the dependability of computing systems? Dependability is the property that a computing system continues to provide its functionality despite the introduction of faults, either accidental faults (design defects, environmental effects, etc.) or maliciously introduced faults (security attacks, external or internal). We have been addressing the dependability challenge through large-scale data analytics applied end-to-end from the small (networked embedded systems, mobile and wearable devices) [e.g., NeurIPS-20, Sensys-20, UsenixSec-20, NDSS-20, DSN-19, UsenixSec-18, S&P-17] to the large (edge and cloud systems, distributed machine learning clusters) [e.g., DSN-20, UsenixATC-20, UsenixATC-19, ICS-19, TDSC-18]. In this talk, I will first give a high-level view of how data analytics has been brought to bear on dependability challenges, and key insights arising from work done by the technical community broadly. Then I will do a deep dive into the problem of configuring complex systems to meet dependability and performance requirements, using data-driven decisions. The first detailed item is in the small: how to perform analytics on streaming video close to the source of the data, such as on an embedded or mobile device, while providing performance guarantees. The second is in the large: how to reconfigure clustered NoSQL databases in the face of changing workloads while preserving availability. Bio: Saurabh Bagchi is a Professor in the School of Electrical and Computer Engineering and the Department of Computer Science at Purdue University in West Lafayette, Indiana. He is the founding Director of a university-wide resiliency center at Purdue called CRISP (2017-present) and co-lead on the WHIN center for IoT testbeds for digital agriculture and advanced manufacturing. He is the recipient of the Alexander von Humboldt Research Award (2018), an Adobe Research award (2017), the AT&T Labs VURI Award (2016), the Google Faculty Award (2015), and the IBM Faculty Award (2014). He serves on the IEEE Computer Society Board of Governors and is a member of the International Federation for Information Processing (IFIP). Saurabh's research interest is in distributed systems and dependable computing. He is proudest of the 21 PhD and about 50 Masters students who have graduated from his research group and who are in various stages of building wonderful careers in industry or academia. In his group, he and his students have far too much fun building and breaking real systems for the greater good. Saurabh received his MS and PhD degrees from the University of Illinois at Urbana-Champaign and his BS degree from the Indian Institute of Technology Kharagpur, all in Computer Science.