國立高雄大學圖資館 |

登入

回首頁

Big data managementdata governance principles for big data analytics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Big data managementPeter Ghavami.
其他題名:	data governance principles for big data analytics /
作者:	Ghavami, Peter.
出版者:	Berlin ;De Gruyter,c2021.
面頁冊數:	1 online resource (xviii, 155 p.) :ill.
標題:	Big data.
電子資源:	https://www.degruyter.com/isbn/9783110664065
ISBN:	9783110664065$q(electronic bk.)

Big data managementdata governance principles for big data analytics /
Ghavami, Peter.

Big data managementdata governance principles for big data analytics /[electronic resource] :Peter Ghavami. - 1st ed. - Berlin ;De Gruyter,c2021. - 1 online resource (xviii, 155 p.) :ill.

Includes bibliographical references and index.

Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world's leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.

Mode of access: Internet via World Wide Web.

In English.

ISBN: 9783110664065$q(electronic bk.)

Standard No.: 10.1515/9783110664065doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45 / G43 2021

Dewey Class. No.: 005.7

Big data managementdata governance principles for big data analytics /
LDR:02309cmm a2200337 a 4500 001 663847
003 DE-B1597
005 20240923072503.0
006 m o d
007 cr cnu---unuuu
008 241219s2021 gw a ob 001 0 eng d
020 $a 9783110664065$q(electronic bk.)
020 $a 9783110664324$q(epub)
020 $z 9783110662917$q(paperback)
024 7 $a 10.1515/9783110664065 $2 doi
035 $a 9783110664065
040 $a DE-B1597 $b eng $c DE-B1597
041 0 $a eng
044 $a gw $c DE
050 4 $a QA76.9.B45 $b G43 2021
082 0 4 $a 005.7 $2 23
100 1 $a Ghavami, Peter. $3 976293
245 1 0 $a Big data management $h [electronic resource] : $b data governance principles for big data analytics / $c Peter Ghavami.
250 $a 1st ed.
260 $a Berlin ; $a Boston : $b De Gruyter, $c c2021.
300 $a 1 online resource (xviii, 155 p.) : $b ill.
504 $a Includes bibliographical references and index.
520 $a Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world's leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.
530 $a Issued also in print.
538 $a Mode of access: Internet via World Wide Web.
546 $a In English.
588 $a Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Jan 2024)
650 0 $a Big data. $3 609582
650 0 $a Data mining. $3 184440
856 4 0 $u https://www.degruyter.com/isbn/9783110664065