Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Laura M. Haas"'
Publikováno v:
Issue 1.
In 2016, the National Academies of Sciences, Engineering, and Medicine of the United States established the Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective. The committee issued a 120-page report in 2018, setting f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::333e45360460852787b082ae47d059b2
https://doi.org/10.1162/99608f92.38f16b68
https://doi.org/10.1162/99608f92.38f16b68
Publikováno v:
The VLDB Journal, 22 (4)
The VLDB Journal, 22 (4)
ISSN:1066-8888
ISSN:0949-877X
ISSN:1066-8888
ISSN:0949-877X
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94813b64d126757a49d85e29e08a7832
http://doc.rero.ch/record/315980/files/778_2012_Article_297.pdf
http://doc.rero.ch/record/315980/files/778_2012_Article_297.pdf
Autor:
Jennifer Widom, Michael J. Franklin, Michael Stonebraker, Volker Markl, Joseph M. Hellerstein, Samuel Madden, Anastasia Ailamaki, Johannes Gehrke, Daniel J. Abadi, Dan Suciu, Christopher Olston, Tova Milo, Philip A. Bernstein, Laura M. Haas, Rakesh Agrawal, Todd Walter, Christopher Ré, Donald Kossmann, Jeffrey Dean, Yannis Ioannidis, AnHai Doan, Jeffrey F. Naughton, Raghu Ramakrishnan, Magdalena Balazinska, Sharad Mehrotra, Michael J. Carey, H. V. Jagadish, Alon Halevy, Surajit Chaudhuri, Beng Chin Ooi
Publikováno v:
Communications of the ACM. 59:92-99
Every few years a group of database researchers meets to discuss the state of database research, its impact on practice, and important new directions. This report summarizes the discussion and conclusions of the eighth such meeting, held October 14-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ab7808d55c8df77b4d8c9a613a6aa41
https://doi.org/10.1145/2845915
https://doi.org/10.1145/2845915
Publikováno v:
ICDE
In the first wave of data science education programs, data engineering topics (systems, scalable algorithms, data management, integration) tended to be de-emphasized in favor of machine learning and statistical modeling. The anecdotal evidence sugges
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c729562ae20a4d4426049f928701404
https://doi.org/10.1109/icde.2017.215
https://doi.org/10.1109/icde.2017.215
Autor:
Laura M. Haas
Publikováno v:
ICDE
Doing data science - extracting insight by analyzing data - is not easy. Data science is used to answer interesting questions that typically involve multiple diverse data sources, many different types of analysis, and often, large and messy data volu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51f480a10d7547235ae85e896bab5fb6
https://doi.org/10.1109/icde.2017.9
https://doi.org/10.1109/icde.2017.9
Publikováno v:
ACM SIGMOD Record. 43:41-48
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::689368ffbd41ac77e65acc65b800c9c6
https://doi.org/10.1145/2694413.2694423
https://doi.org/10.1145/2694413.2694423
Publikováno v:
Scopus-Elsevier
In this paper, we present Vagabond , a system that uses a novel holistic approach to help users to understand and debug data exchange scenarios. Developing such a scenario is a complex and labor-intensive process where errors are often only revealed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce30d42c22ca049275ae59096cf15bbf
https://doi.org/10.14778/3402755.3402776
https://doi.org/10.14778/3402755.3402776
Publikováno v:
Proceedings of the VLDB Endowment. 3:1314-1325
Though partially automated, developing schema mappings remains a complex and potentially error-prone task. In this paper, we present TRAMP (TRAnsformation Mapping Provenance), an extensive suite of tools supporting the debugging and tracing of schema
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdbd6d9c09d31f128edfd8900057c869
https://doi.org/10.14778/1920841.1921003
https://doi.org/10.14778/1920841.1921003
Publikováno v:
Proceedings of the VLDB Endowment. 3:232-243
There are many academic and commercial stream processing engines (SPEs) today, each of them with its own execution semantics. This variation may lead to seemingly inexplicable differences in query results. In this paper, we present SECRET, a model of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edd478c8a31564f1c7e5eda52c49dd0a
https://doi.org/10.14778/1920841.1920874
https://doi.org/10.14778/1920841.1920874
Publikováno v:
Proceedings of the VLDB Endowment. 3:1621-1624
Today's data integration systems must be flexible enough to support the typical iterative and incremental process of integration, and may need to scale to hundreds of data sources. In this work we present a novel data integration system that offers g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2f2624c05e01c6de0424dd6c717bb7a
https://doi.org/10.14778/1920841.1921055
https://doi.org/10.14778/1920841.1921055