Abstract
Big data analytics in recent years had developed lightning fast applications that deal with predictive analysis of huge volumes of data in domains of finance, health, weather, travel, marketing and more. Business analysts take their decisions using the statistical analysis of the available data pulled in from social media, user surveys, blogs and internet resources. Customer sentiment has to be taken into account for designing, launching and pricing a product to be inducted into the market and the emotions of the consumers changes and is influenced by several tangible and intangible factors. The possibility of using Big data analytics to present data in a quickly viewable format giving different perspectives of the same data is appreciated in the field of finance and health, where the advent of decision support system is possible in all aspects of their working. Cognitive computing and artificial intelligence are making big data analytical algorithms to think more on their own, leading to come out with Big data agents with their own functionalities.
Reference80 articles.
1. Data management in the cloud: Limitations and opportunities.;D. J.Abadi;IEEE Data Eng. Bull.,2009
2. Ag, B. (2004, May). Introduction of the Radial Basis Function (RBF) Networks. Online Symposium for Electronics Engineers, DSP Algorithms: Multimedia. Retrieved from http://www. osee. net
3. Mining association rules between sets of items in large databases
4. Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Big data analytics and innovation in e-commerce: current insights and future directions;Journal of Financial Services Marketing;2023-05-26
2. Introduction to Predictive Analytics;Predictive Analytics for Mechanical Engineering: A Beginners Guide;2023
3. Business Intelligence and Social Media Analytics;Contributions to Management Science;2021