Biography

Presenters

Dr. Divyakant Agrawal

Dr. Divyakant Agrawal is a Professor of Computer Science at the University of California at Santa Barbara. His research expertise is in the areas of database systems, distributed computing, data warehousing, and large-scale information systems. From January 2006 through December 2007, Dr. Agrawal served as VP of Data Solutions and Advertising Systems at the Internet Search Company ASK.com. While at ASK.com, Dr. Agrawal was the Chief Architect for building the next-generation Business Intelligence and Data Warehousing system. In addition, he developed revenue-sensitive products at ASK.com by applying data-mining and machine-learning technologies over ASK.com’s historical data. Dr. Agrawal also served as a Visiting Senior Research Scientist at the NEC Laboratories of America in Cupertino, CA from 1997 to 2009. He is currently a Visiting Professor at the School of Computing at the National University of Singapore (Summer'2010). During his professional career, Dr. Agrawal has served extensively on the Program Committees of
International Conferences, Symposia, and Workshops and served as an editor of the journal of Distributed and Parallel Databases (1993-2008), the VLDB journal (2003-2008) and currently serves on the editorial board of the Proceedings of the VLDB. He recently served as the Program Chair of the 2010 ACM International Conference on Management of Data and is currently serving as the General Chair of the 2010 ACM SIGSPATIAL Conference on Advances in Geographical Information Systems. Dr. Agrawal's research philosophy is to work on data management problem that have both practical as well as theoretical impact. He has published approximately 300 research manuscripts in prestigious forums (journals, conferences, symposia, and workshops) on wide range of topics related to data management and distributed systems.

Sudipto Das

Sudipto Das received his B. Engg. degree in Computer Science and Engineering from Jadavpur University, India in 2006 and was awarded the TCS-JU best student award for 2006. He is currently a PhD candidate in the Department of Computer Science at University of California, Santa Barbara. His research interests lie in the area of scalable data management in cloud computing infrastructures. He is specifically interested in update intensive and transactional systems for cloud platforms that scale out while providing the developers consistency that they can reason about. He is the recipient of UCSB Computer Science Outstanding Teaching Assistant award for Fall 2008 and the UCSB graduate division Dissertation Fellowship for 2011. He is a student member of ACM and IEEE.

Amr El Abbadi

Amr El Abbadi received his PhD degree in Computer Science from Cornell University in 1987. He is currently a Professor and Chair of the Department of Computer Science at the University of California, Santa Barbara. He has held visiting professor positions at the University of Campinas in Brazil, IBM Almaden Research Center, the Swedish Institute of Computer Science in Stockholm, and at IRISA at the University of Rennes in France. He was Vice Chair of ICDCS 1999, Vice Chair for ICDE 2002, the Americas Program Chair for VLDB 2000, and is the Program Chair for SIGSPATIAL 2010 and Program co-chair of ACM SOCC 2011. He served as a board member of the VLDB Endowment from 2002 to 2008. In 2007, Prof. El Abbadi received the UCSB Senate Outstanding Mentorship Award for his excellence in mentoring graduate students. His research interests lie in the broad area of scalable database and distributed systems. He is a senior member of IEEE and ACM.

Title: Big Data and Cloud Computing: New Wine or just New Bottles?

Cloud computing is an extremely successful paradigm of service oriented computing, and has revolutionized the way computing infrastructure is used. This success has seen a proliferation in the number of applications which leverage various cloud platforms, resulting in a tremendous increase in the scale of the data generated as well as consumed by such applications. Scalable database management systems – both for update intensive application workloads, as well as decision support systems for descriptive and deep analytics – are thus a critical part of the cloud infrastructure. The quest for conquering the challenges posed by the management of big data has led to a plethora of systems. This tutorial aims to clarify some of the critical concepts in the design space of big data and cloud computing such as: the appropriate systems for a specific set of application requirements, the research challenges in data management for the cloud, and what is novel in the cloud for database researchers? We also aim to address one basic question: Whether cloud computing poses new challenges in scalable data management or it is just a reincarnation of old problems? We provide a comprehensive background study of state-of-the-art systems for scalable data management and analysis. We also identify the critical aspects in the design of different systems and the applicability and scope of these systems. A thorough understanding of current solutions and a precise characterization of the design space are essential for clearing the "cloudy skies of data management" and ensuring the success of DBMSs in the cloud, thus emulating the success enjoyed by relational databases in traditional enterprise settings.

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