%0 Journal Article %1 AbadiAgrawalEtAl16cacm %A Abadi, Daniel %A Agrawal, Rakesh %A Ailamaki, Anastasia %A Balazinska, Magdalena %A Bernstein, Philip A. %A Carey, Michael J. %A Chaudhuri, Surajit %A Chaudhuri, Surajit %A Dean, Jeffrey %A Doan, AnHai %A Franklin, Michael J. %A Gehrke, Johannes %A Haas, Laura M. %A Halevy, Alon Y. %A Hellerstein, Joseph M. %A Ioannidis, Yannis E. %A Jagadish, H. V. %A Kossmann, Donald %A Madden, Samuel %A Mehrotra, Sharad %A Milo, Tova %A Naughton, Jeffrey F. %A Ramakrishnan, Raghu %A Markl, Volker %A Olston, Christopher %A Ooi, Beng Chin %A Ré, Christopher %A Suciu, Dan %A Stonebraker, Michael %A Walter, Todd %A Widom, Jennifer %D 2016 %J Communications of the ACM %K 01801 acm paper ai database data pattern recognition analysis zzz.big %N 2 %P 92--99 %R 10.1145/2845915 %T The Beckman Report on Database Research %V 59 %X Database researchers paint big data as a defining challenge. To make the most of the enormous opportunities at hand will require focusing on five research areas: Developing scalable data infrastructures, coping with increased diversity in both data and data management, addressing the end-to-end data-to-knowledge pipeline, responding to the adoption of cloud-based computing, and accomodating the many and changing roles of individuals in the data life cycle.

@article{AbadiAgrawalEtAl16cacm, abstract = {Database researchers paint big data as a defining challenge. To make the most of the enormous opportunities at hand will require focusing on five research areas: Developing scalable data infrastructures, coping with increased diversity in both data and data management, addressing the end-to-end data-to-knowledge pipeline, responding to the adoption of cloud-based computing, and accomodating the many and changing roles of individuals in the data life cycle.}, added-at = {2016-05-21T13:17:44.000+0200}, author = {Abadi, Daniel and Agrawal, Rakesh and Ailamaki, Anastasia and Balazinska, Magdalena and Bernstein, Philip A. and Carey, Michael J. and Chaudhuri, Surajit and Chaudhuri, Surajit and Dean, Jeffrey and Doan, AnHai and Franklin, Michael J. and Gehrke, Johannes and Haas, Laura M. and Halevy, Alon Y. and Hellerstein, Joseph M. and Ioannidis, Yannis E. and Jagadish, H. V. and Kossmann, Donald and Madden, Samuel and Mehrotra, Sharad and Milo, Tova and Naughton, Jeffrey F. and Ramakrishnan, Raghu and Markl, Volker and Olston, Christopher and Ooi, Beng Chin and R\'{e}, Christopher and Suciu, Dan and Stonebraker, Michael and Walter, Todd and Widom, Jennifer}, biburl = {https://www.bibsonomy.org/bibtex/232dd8ec09ddd43338a39639e4dbabec4/flint63}, doi = {10.1145/2845915}, file = {ACM Digital Library:2016/AbadiAgrawalEtAl16cacm.pdf:PDF}, groups = {public}, interhash = {d9bc36cf23ebef4d8b67371247904ad3}, intrahash = {32dd8ec09ddd43338a39639e4dbabec4}, issn = {0001-0782}, journal = {Communications of the ACM}, keywords = {01801 acm paper ai database data pattern recognition analysis zzz.big}, month = {#feb#}, number = 2, pages = {92--99}, timestamp = {2018-04-16T11:48:47.000+0200}, title = {The {Beckman} Report on Database Research}, username = {flint63}, volume = 59, year = 2016 }