Big Data
Principles and Paradigms
Nonfiction, Computers, Database Management, Data Processing, General Computing
| Author: | ISBN: | 9780128093467 | |
| Publisher: | Elsevier Science | Publication: | June 7, 2016 |
| Imprint: | Morgan Kaufmann | Language: | English |
| Author: | |
| ISBN: | 9780128093467 |
| Publisher: | Elsevier Science |
| Publication: | June 7, 2016 |
| Imprint: | Morgan Kaufmann |
| Language: | English |
Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.
To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.
- Covers computational platforms supporting Big Data applications
- Addresses key principles underlying Big Data computing
- Examines key developments supporting next generation Big Data platforms
- Explores the challenges in Big Data computing and ways to overcome them
- Contains expert contributors from both academia and industry
Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.
To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.
- Covers computational platforms supporting Big Data applications
- Addresses key principles underlying Big Data computing
- Examines key developments supporting next generation Big Data platforms
- Explores the challenges in Big Data computing and ways to overcome them
- Contains expert contributors from both academia and industry
