Obtaining value from big data for service delivery
1. Introduction -- 2. Applications of big data to service delivery -- 3. Analyzing big data for successful results -- 4. Big data infrastructure, a technical architecture overview -- 5. Building an effective big data organization -- 6. Issues and challenges in big data and analytics -- 7. Conclusion...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
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New York, New York (222 East 46th Street, New York, NY 10017)
Business Expert Press
2016
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| Ausgabe: | First edition |
| Schriftenreihe: | Service systems and innovations in business and society collection
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| 100 | 1 | |a Kaisler, Stephen H. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Obtaining value from big data for service delivery |c Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, and William H. Money |
| 250 | |a First edition | ||
| 264 | 1 | |a New York, New York (222 East 46th Street, New York, NY 10017) |b Business Expert Press |c 2016 | |
| 300 | |a Online-Ressource (xxi, 176 pages) | ||
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| 490 | 0 | |a Service systems and innovations in business and society collection | |
| 500 | |a Includes bibliographical references (pages 161-168) and index | ||
| 520 | |a 1. Introduction -- 2. Applications of big data to service delivery -- 3. Analyzing big data for successful results -- 4. Big data infrastructure, a technical architecture overview -- 5. Building an effective big data organization -- 6. Issues and challenges in big data and analytics -- 7. Conclusion: capturing the value of big data projects -- Appendix A. Methods-based analytics taxonomy -- References -- Further reading -- Glossary -- Index | ||
| 520 | |a Big 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), healthcare, 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 analyze it; 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 | ||
| 650 | 4 | |a Service-oriented architecture (Computer science) | |
| 650 | 4 | |a Big data | |
| 700 | 1 | |a Armour, Frank. |4 aut | |
| 700 | 1 | |a Espinosa, J. Alberto. |4 aut | |
| 700 | 1 | |a Money, William H. |4 aut | |
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| isbn | 9781631572234 9781631572227 |
| language | English |
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| spelling | Kaisler, Stephen H. Verfasser aut Obtaining value from big data for service delivery Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, and William H. Money First edition New York, New York (222 East 46th Street, New York, NY 10017) Business Expert Press 2016 Online-Ressource (xxi, 176 pages) txt rdacontent c rdamedia cr rdacarrier Service systems and innovations in business and society collection Includes bibliographical references (pages 161-168) and index 1. Introduction -- 2. Applications of big data to service delivery -- 3. Analyzing big data for successful results -- 4. Big data infrastructure, a technical architecture overview -- 5. Building an effective big data organization -- 6. Issues and challenges in big data and analytics -- 7. Conclusion: capturing the value of big data projects -- Appendix A. Methods-based analytics taxonomy -- References -- Further reading -- Glossary -- Index Big 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), healthcare, 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 analyze it; 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 Service-oriented architecture (Computer science) Big data Armour, Frank. aut Espinosa, J. Alberto. aut Money, William H. aut Erscheint auch als Druck-Ausgabe 9781631572227 http://portal.igpublish.com/iglibrary/search/BEPB0000448.html Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Kaisler, Stephen H. Armour, Frank Espinosa, J. Alberto Money, William H. Obtaining value from big data for service delivery Service-oriented architecture (Computer science) Big data |
| title | Obtaining value from big data for service delivery |
| title_auth | Obtaining value from big data for service delivery |
| title_exact_search | Obtaining value from big data for service delivery |
| title_full | Obtaining value from big data for service delivery Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, and William H. Money |
| title_fullStr | Obtaining value from big data for service delivery Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, and William H. Money |
| title_full_unstemmed | Obtaining value from big data for service delivery Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, and William H. Money |
| title_short | Obtaining value from big data for service delivery |
| title_sort | obtaining value from big data for service delivery |
| topic | Service-oriented architecture (Computer science) Big data |
| topic_facet | Service-oriented architecture (Computer science) Big data |
| url | http://portal.igpublish.com/iglibrary/search/BEPB0000448.html |
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