A demo of the data civilizer system

Raul Castro Fernandez; Dong Deng; Essam Mansour; Abdulhakim A. Qahtan; Wenbo Tao; Ziawasch Abedjan; Ahmed Elmagarmid; Ihab F. Ilyas; Samuel Madden; Mourad Ouzzani; Michael Stonebraker; Nan Tang

doi:10.1145/3035918.3058740

A demo of the data civilizer system

Raul Castro Fernandez, Dong Deng, Essam Mansour, Abdulhakim A. Qahtan, Wenbo Tao, Ziawasch Abedjan, Ahmed Elmagarmid, Ihab F. Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang

Qatar Computing Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Citations (Scopus)

Abstract

Finding relevant data for a specific task from the numerous data sources available in any organization is a daunting task. This is not only because of the number of possible data sources where the data of interest resides, but also due to the data being scattered all over the enterprise and being typically dirty and inconsistent. In practice, data scientists are routinely reporting that the majority (more than 80%) of their effort is spent finding, cleaning, integrating, and accessing data of interest to a task at hand. We propose to demonstrate Data Civilizer to ease the pain faced in analyzing data "in the wild". Data Civilizer is an end-to-end big data management system with components for data discovery, data integration and stitching, data cleaning, and querying data from a large variety of storage engines, running in large enterprises.

Original language	English
Title of host publication	SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data
Publisher	Association for Computing Machinery
Pages	1639-1642
Number of pages	4
ISBN (Electronic)	9781450341974
DOIs	https://doi.org/10.1145/3035918.3058740
Publication status	Published - 9 May 2017
Event	2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017 - Chicago, United States Duration: 14 May 2017 → 19 May 2017

Publication series

Name	Proceedings of the ACM SIGMOD International Conference on Management of Data
Volume	Part F127746
ISSN (Print)	0730-8078

Conference

Conference	2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017
Country/Territory	United States
City	Chicago
Period	14/05/17 → 19/05/17

Access to Document

10.1145/3035918.3058740

Cite this

Fernandez, R. C., Deng, D., Mansour, E., Qahtan, A. A., Tao, W., Abedjan, Z., Elmagarmid, A., Ilyas, I. F., Madden, S., Ouzzani, M., Stonebraker, M., & Tang, N. (2017). A demo of the data civilizer system. In SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data (pp. 1639-1642). (Proceedings of the ACM SIGMOD International Conference on Management of Data; Vol. Part F127746). Association for Computing Machinery. https://doi.org/10.1145/3035918.3058740

@inproceedings{46abafc83efc4c64b6bcd53615da1327,

title = "A demo of the data civilizer system",

abstract = "Finding relevant data for a specific task from the numerous data sources available in any organization is a daunting task. This is not only because of the number of possible data sources where the data of interest resides, but also due to the data being scattered all over the enterprise and being typically dirty and inconsistent. In practice, data scientists are routinely reporting that the majority (more than 80%) of their effort is spent finding, cleaning, integrating, and accessing data of interest to a task at hand. We propose to demonstrate Data Civilizer to ease the pain faced in analyzing data {"}in the wild{"}. Data Civilizer is an end-to-end big data management system with components for data discovery, data integration and stitching, data cleaning, and querying data from a large variety of storage engines, running in large enterprises.",

author = "Fernandez, {Raul Castro} and Dong Deng and Essam Mansour and Qahtan, {Abdulhakim A.} and Wenbo Tao and Ziawasch Abedjan and Ahmed Elmagarmid and Ilyas, {Ihab F.} and Samuel Madden and Mourad Ouzzani and Michael Stonebraker and Nan Tang",

note = "Publisher Copyright: {\textcopyright} 2017 ACM.; 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017 ; Conference date: 14-05-2017 Through 19-05-2017",

year = "2017",

month = may,

day = "9",

doi = "10.1145/3035918.3058740",

language = "English",

series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",

publisher = "Association for Computing Machinery",

pages = "1639--1642",

booktitle = "SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data",

address = "United States",

}

Fernandez, RC, Deng, D, Mansour, E, Qahtan, AA, Tao, W, Abedjan, Z, Elmagarmid, A, Ilyas, IF, Madden, S, Ouzzani, M, Stonebraker, M & Tang, N 2017, A demo of the data civilizer system. in SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. Proceedings of the ACM SIGMOD International Conference on Management of Data, vol. Part F127746, Association for Computing Machinery, pp. 1639-1642, 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017, Chicago, United States, 14/05/17. https://doi.org/10.1145/3035918.3058740

A demo of the data civilizer system. / Fernandez, Raul Castro; Deng, Dong; Mansour, Essam et al.
SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. Association for Computing Machinery, 2017. p. 1639-1642 (Proceedings of the ACM SIGMOD International Conference on Management of Data; Vol. Part F127746).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A demo of the data civilizer system

AU - Fernandez, Raul Castro

AU - Deng, Dong

AU - Mansour, Essam

AU - Qahtan, Abdulhakim A.

AU - Tao, Wenbo

AU - Abedjan, Ziawasch

AU - Elmagarmid, Ahmed

AU - Ilyas, Ihab F.

AU - Madden, Samuel

AU - Ouzzani, Mourad

AU - Stonebraker, Michael

AU - Tang, Nan

PY - 2017/5/9

Y1 - 2017/5/9

N2 - Finding relevant data for a specific task from the numerous data sources available in any organization is a daunting task. This is not only because of the number of possible data sources where the data of interest resides, but also due to the data being scattered all over the enterprise and being typically dirty and inconsistent. In practice, data scientists are routinely reporting that the majority (more than 80%) of their effort is spent finding, cleaning, integrating, and accessing data of interest to a task at hand. We propose to demonstrate Data Civilizer to ease the pain faced in analyzing data "in the wild". Data Civilizer is an end-to-end big data management system with components for data discovery, data integration and stitching, data cleaning, and querying data from a large variety of storage engines, running in large enterprises.

AB - Finding relevant data for a specific task from the numerous data sources available in any organization is a daunting task. This is not only because of the number of possible data sources where the data of interest resides, but also due to the data being scattered all over the enterprise and being typically dirty and inconsistent. In practice, data scientists are routinely reporting that the majority (more than 80%) of their effort is spent finding, cleaning, integrating, and accessing data of interest to a task at hand. We propose to demonstrate Data Civilizer to ease the pain faced in analyzing data "in the wild". Data Civilizer is an end-to-end big data management system with components for data discovery, data integration and stitching, data cleaning, and querying data from a large variety of storage engines, running in large enterprises.

UR - http://www.scopus.com/inward/record.url?scp=85021185176&partnerID=8YFLogxK

U2 - 10.1145/3035918.3058740

DO - 10.1145/3035918.3058740

M3 - Conference contribution

AN - SCOPUS:85021185176

T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data

SP - 1639

EP - 1642

BT - SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data

PB - Association for Computing Machinery

T2 - 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017

Y2 - 14 May 2017 through 19 May 2017

ER -

A demo of the data civilizer system

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this