Large volumes of data are analyzed using big data analytics to find undiscovered trends, connections, and perhaps other revelations. With the new technological advances in the present, one can capture and evaluate their data and obtain insights from it almost immediately, whereas this process would take longer and be less effective with more conventional business intelligence tools (Pappas et al., 2021). Businesses may tap their content and use big data analytics to find new possibilities. This results in wiser company decisions, more effective operations, greater profitability, and happier clients (Mikalef et al., 2019). Businesses that combine big data with sophisticated analytics benefit in a variety of ways.
This include cost savings where the Big Data Analytics majorly concentrates on the expense of keeping vast amounts of data. Big data technologies like cloud-based analytics can drastically cut that cost by, for example, using a data warehouse (Wang et al., 2022). Additionally, big data analytics assists businesses in finding ways to operate more effectively. Quicker and more accurate decision-making (Hariri et al., 2019). Businesses can quickly evaluate information in order to make quick, intelligent choices because of in-memory analytics’ speed and the capacity to examine new forms of data, including concurrent access of data from IoT (Hariri et al., 2019). Creating and promoting new product lines and solutions. Businesses may offer consumers what they require whenever they require it by using analytics to determine their demands and level of satisfaction. Big data analytics give more businesses the chance to create cutting-edge new goods that cater to the shifting wants of their clients (Dubey et al., 2021). The Big Data Analytics to help out in price reduction. In order to increase profits, businesses may choose fee structures that predict and incorporate data from various data sources. Risk control can also be facilitated by these data analytics (Dubey et al., 2021). Efficient risk mitigation techniques can be developed using big data analytics to find new dangers in data trends.
References
Dubey, R., Bryde, D. J., Graham, G., Foropon, C., Kumari, S., & Gupta, O. (2021). The role of Alliance Management, Big Data Analytics and information visibility on new-product development capability. Annals of Operations Research. Web.
Hariri, R. H., Fredericks, E. M., & Bowers, K. M. (2019). Uncertainty in big data analytics: Survey, opportunities, and challenges. Journal of Big Data, 6(1). Web.
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big Data Analytics and firm performance: Findings from a mixed-method approach. Journal of Business Research, 98, 261–276. Web.
Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2021). Correction to: Big Data and business analytics ecosystems: Paving the way towards Digital Transformation and Sustainable Societies. Information Systems and e-Business Management, 19(4), 1355–1355. Web.
Wang, J., Xu, C., Zhang, J., & Zhong, R. (2022). Big Data Analytics for Intelligent Manufacturing Systems: A Review. Journal of Manufacturing Systems, 62, 738–752. Web.