Obtaining value from big data for service systems. Volume II, Big data technology /
Kaisler, Stephen H.,
Obtaining value from big data for service systems. Volume II, Big data technology / Big data technology Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, William H. Money. - Second edition. - 1 online resource (xvii, 103 pages) : illustrations - Service systems and innovations in business and society collection, 2326-2699 . - Service systems and innovations in business and society collection. .
Includes bibliographies and index.
Chapter 1. Big data infrastructure-a technical architecture overview -- Chapter 2. Issues and challenges in big data and analytics -- Chapter 3. Conclusion.
Access restricted to authorized users and institutions.
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), 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.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781949991475
Big data.
Data mining.
Service-oriented architecture. Analytic science. Big data. Business analytics. Business intelligence. Data science. Descriptive analytics. Enterprise architecture. NoSQL. Predictive analytics. Service delivery.
[genre]
Electronic books.
QA76.9.B45
Obtaining value from big data for service systems. Volume II, Big data technology / Big data technology Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, William H. Money. - Second edition. - 1 online resource (xvii, 103 pages) : illustrations - Service systems and innovations in business and society collection, 2326-2699 . - Service systems and innovations in business and society collection. .
Includes bibliographies and index.
Chapter 1. Big data infrastructure-a technical architecture overview -- Chapter 2. Issues and challenges in big data and analytics -- Chapter 3. Conclusion.
Access restricted to authorized users and institutions.
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), 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.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781949991475
Big data.
Data mining.
Service-oriented architecture. Analytic science. Big data. Business analytics. Business intelligence. Data science. Descriptive analytics. Enterprise architecture. NoSQL. Predictive analytics. Service delivery.
[genre]
Electronic books.
QA76.9.B45