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Big data analytics: turning big data into big money
Abstract
Unique insights to implement big data analytics and reap big returns to your bottom lineFocusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantageTakes an in-depth look at the financial value of big data analyticsOffers tools and best practices for working with big dataOnce the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.
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Citations
Cited by
Big data analytics in healthcare: promise and potential
Raghupathi, W., & Raghupathi, V. (2014) · Health Information Science and Systems · doi:10.1186/2047-2501-2-3 · Cited by 3,034
Big-data applications in the government sector
Kim, G.-H., Trimi, S., & Chung, J.-H. (2014) · Communications of the ACM · doi:10.1145/2500873 · Cited by 632
Akter, S., Michael, K., Uddin, M. R., McCarthy, G., & Rahman, M. (2022) · Annals of Operations Research · doi:10.1007/s10479-020-03620-w · Cited by 587
The role of administrative data in the big data revolution in social science research
Connelly, R., Playford, C. J., Gayle, V., & Dibben, C. (2016) · Social Science Research · doi:10.1016/j.ssresearch.2016.04.015 · Cited by 330
Contextual anomaly detection framework for big sensor data
Hayes, M. A., & Capretz, M. A. (2015) · Journal of Big Data · doi:10.1186/s40537-014-0011-y · Cited by 149
Metadata
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 2013-04-17
- Volume
- 50
- Issue
- 09
- Pages
- 50-5095-50-5095
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W575942744
- Cited by
- 199
- References
- 0
- Type
- book review
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
