Organizational data mining: leveraging enterprise data resources for optimal performance
Mountains of business data are piling up in organizations every day. These organizations collect data from multiple sources, both internal and external. These sources include legacy systems, customer relationship management and enterprise resource planning applications, online and e-commerce systems...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pa
IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
c2004
|
| Schlagworte: | |
| Online-Zugang: | DE-898 DE-706 DE-1050 DE-1049 DE-83 Volltext |
| Zusammenfassung: | Mountains of business data are piling up in organizations every day. These organizations collect data from multiple sources, both internal and external. These sources include legacy systems, customer relationship management and enterprise resource planning applications, online and e-commerce systems, government organizations and business suppliers and partners. A recent study from the University of California at Berkeley found the amount of data organizations collect and store in enterprise databases doubles every year, and slightly more than half of this data will consist of "reference information," which is the kind of information strategic business applications and decision support systems demand (Kestelyn, 2002). Terabyte-sized (1,000 megabytes) databases are commonplace in organizations today, and this enormous growth will make petabyte-sized databases (1,000 terabytes) a reality within the next few years (Whiting, 2002). By 2004 the Gartner Group estimates worldwide data volumes will be 30 times those of 1999, which translates into more data having been produced in the last 30 years than during the previous 5,000 (Wurman, 1989) |
| Beschreibung: | Includes bibliographical references and index. - Title from ebook home page (viewed on July 13, 2010) |
| Beschreibung: | 1 Online-Ressource (electronic texts (xiii, 371 p. ill.)) digital files |
| DOI: | 10.4018/978-1-59140-134-6 |
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| 245 | 1 | 0 | |a Organizational data mining |b leveraging enterprise data resources for optimal performance |c Hamid R. Nemati, Christopher D. Barko |
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| 520 | |a Mountains of business data are piling up in organizations every day. These organizations collect data from multiple sources, both internal and external. These sources include legacy systems, customer relationship management and enterprise resource planning applications, online and e-commerce systems, government organizations and business suppliers and partners. A recent study from the University of California at Berkeley found the amount of data organizations collect and store in enterprise databases doubles every year, and slightly more than half of this data will consist of "reference information," which is the kind of information strategic business applications and decision support systems demand (Kestelyn, 2002). Terabyte-sized (1,000 megabytes) databases are commonplace in organizations today, and this enormous growth will make petabyte-sized databases (1,000 terabytes) a reality within the next few years (Whiting, 2002). By 2004 the Gartner Group estimates worldwide data volumes will be 30 times those of 1999, which translates into more data having been produced in the last 30 years than during the previous 5,000 (Wurman, 1989) | ||
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| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| doi_str_mv | 10.4018/978-1-59140-134-6 |
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| index_date | 2024-07-03T19:36:12Z |
| indexdate | 2024-08-23T01:08:46Z |
| institution | BVB |
| language | English |
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| spelling | Nemati, Hamid R. 1958- Verfasser aut Organizational data mining leveraging enterprise data resources for optimal performance Hamid R. Nemati, Christopher D. Barko Hershey, Pa IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) c2004 1 Online-Ressource (electronic texts (xiii, 371 p. ill.)) digital files txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index. - Title from ebook home page (viewed on July 13, 2010) Mountains of business data are piling up in organizations every day. These organizations collect data from multiple sources, both internal and external. These sources include legacy systems, customer relationship management and enterprise resource planning applications, online and e-commerce systems, government organizations and business suppliers and partners. A recent study from the University of California at Berkeley found the amount of data organizations collect and store in enterprise databases doubles every year, and slightly more than half of this data will consist of "reference information," which is the kind of information strategic business applications and decision support systems demand (Kestelyn, 2002). Terabyte-sized (1,000 megabytes) databases are commonplace in organizations today, and this enormous growth will make petabyte-sized databases (1,000 terabytes) a reality within the next few years (Whiting, 2002). By 2004 the Gartner Group estimates worldwide data volumes will be 30 times those of 1999, which translates into more data having been produced in the last 30 years than during the previous 5,000 (Wurman, 1989) Knowledge management Data mining Business Data processing Barko, Christopher D. 1968- ctb https://doi.org/10.4018/978-1-59140-134-6 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Nemati, Hamid R. 1958- Organizational data mining leveraging enterprise data resources for optimal performance Knowledge management Data mining Business Data processing |
| title | Organizational data mining leveraging enterprise data resources for optimal performance |
| title_auth | Organizational data mining leveraging enterprise data resources for optimal performance |
| title_exact_search | Organizational data mining leveraging enterprise data resources for optimal performance |
| title_exact_search_txtP | Organizational data mining leveraging enterprise data resources for optimal performance |
| title_full | Organizational data mining leveraging enterprise data resources for optimal performance Hamid R. Nemati, Christopher D. Barko |
| title_fullStr | Organizational data mining leveraging enterprise data resources for optimal performance Hamid R. Nemati, Christopher D. Barko |
| title_full_unstemmed | Organizational data mining leveraging enterprise data resources for optimal performance Hamid R. Nemati, Christopher D. Barko |
| title_short | Organizational data mining |
| title_sort | organizational data mining leveraging enterprise data resources for optimal performance |
| title_sub | leveraging enterprise data resources for optimal performance |
| topic | Knowledge management Data mining Business Data processing |
| topic_facet | Knowledge management Data mining Business Data processing |
| url | https://doi.org/10.4018/978-1-59140-134-6 |
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