000 04453nam a2200673 i 4500
001 9781949991475
003 BEP
005 20241023114914.0
006 m eo d
007 cr cn |||m|||a
008 190417s2019 nyua fob 001 0 eng d
020 _a9781949991475
_qe-book
035 _a(OCoLC)1106364808
035 _a(CaBNVSL)slc46082492
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aQA76.9.B45
100 1 _aKaisler, Stephen H.,
_eauthor.
245 1 0 _aObtaining value from big data for service systems.
_nVolume II,
_pBig data technology /
_cStephen H. Kaisler, Frank Armour, J. Alberto Espinosa, William H. Money.
246 3 0 _aBig data technology
250 _aSecond edition.
264 1 _aNew York, New York (222 East 46th Street, New York, NY 10017) :
_bBusiness Expert Press,
_c[(c)2019.]
300 _a1 online resource (xvii, 103 pages) :
_billustrations
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _adata file
_2rda
490 1 _aService systems and innovations in business and society collection,
_x2326-2699
504 _a2
505 0 _aChapter 1. Big data infrastructure-a technical architecture overview --
_tChapter 2. Issues and challenges in big data and analytics --
_tChapter 3. Conclusion.
506 _aAccess restricted to authorized users and institutions.
520 3 _aBig data is an emerging phenomenon that has enormous implications and impacts upon business strategy, profitability, and process improvements. All service systems generate big data these days, especially human-centered service systems such as government (including cities), health care, education, retail, finance, and so on. It has been characterized as the collection, analysis, and use of data characterized by the five Vs: volume, velocity, variety, veracity, and value (of data). As the plethora of data sources grows from sensors, social media, and electronic transactions, new methods for collecting or acquiring, integrating, processing, analyzing, understanding, and visualizing data to provide actionable information and support integrated and timely senior and executive decision making are required. The discipline of applying analytic processes to find and combine new sources of data and extract hidden crucial decision-making information from the oceans of data is rapidly developing, but requires expertise to apply in ways that will yield useful, actionable results for service organizations. Many service-oriented organizations that are just beginning to invest in big data collection, storage, and analysis need to address the numerous issues and challenges that abound - technological, managerial, and legal. Other organizations that have begun to use new data tools and techniques must keep up with the rapidly changing and snowballing work in the field. This booklet will help middle, senior, and executive managers to understand what big data is: how to recognize, collect, process, and analyzeit; how to store and manage it; how to obtain useful information from it; and how to assess its contribution to operational, tactical, and strategic decision making in service-oriented organizations.
530 _a2
_ub
530 _aAlso available in printing.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat reader.
588 _aDescription based on PDF viewed 06/05/2019.
650 0 _aBig data.
650 0 _aData mining.
653 _aService-oriented architecture.
653 _aAnalytic science.
653 _aBig data.
653 _aBusiness analytics.
653 _aBusiness intelligence.
653 _aData science.
653 _aDescriptive analytics.
653 _aEnterprise architecture.
653 _aNoSQL.
653 _aPredictive analytics.
653 _aService delivery.
655 0 _a[genre]
655 0 _aElectronic books.
700 1 _aArmour, Frank,
_eauthor.
700 1 _aEspinosa, J. Alberto,
_eauthor.
700 1 _aMoney, William H.,
_eauthor.
776 0 8 _iPrint version:
_z9781949991468
830 0 _aService systems and innovations in business and society collection.
_x2326-2699
856 4 0 _uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000899.html
942 _2lcc
_bCIU
_cOB
_eBEP
_QOL
_zBEP9781949991475
999 _c74066
_d74066
902 _c1
_dCynthia Snell