AN OVERVIEW OF TRENDS AND TECHNIQUES IN PREDICTIVE ANALYTICS

Authors

  • Naga Sujana Kakumanu Research Scholar, Department of GSBH, GUAM (Deemed to be University), Hyderabad Campus
  • Dr. P. Sridhar Assistant Professor, Department of GSBH, GUAM (Deemed to be University), Hyderabad Campus
  • Bhargavi Mullapudi Research Scholar, Department of GSBH, GUAM (Deemed to be University), Hyderabad Campus

Keywords:

Predictive Analysis, Methodologies, Applications

Abstract

The term "predictive analytics" refers to statistical and analytical methods. This phrase was created using statistics, machine learning, database methods, and optimization techniques. Its roots may be traced all the way back to classical statistics. It creates forecasts using both current and historical data. Predictive analytics algorithms may be used to predict unpredictable behavior and future occurrences. To assign a score, predictive analytics approaches will be employed. A larger number suggests a greater chance of an event occurring, whereas a lower number indicates a lower chance. These frameworks tackle a range of commercial and scientific problems by analyzing historical and transactional data trends. These models assist in identifying the risks and opportunities faced by each customer, employee, or management in a business. As interest in decision-support solutions has grown, predictive analytics models have risen to the top. In this article, we'll go through the methodology, techniques, and applications of predictive analytics.

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Published

2022-12-31

How to Cite

Sujana Kakumanu, N. ., Sridhar, D. P. ., & Mullapudi, B. (2022). AN OVERVIEW OF TRENDS AND TECHNIQUES IN PREDICTIVE ANALYTICS. The Journal of Contemporary Issues in Business and Government, 28(4), 952–959. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/2621

Issue

Vol. 28 No. 4 (2022): The journal of contemporary issues in business and government

Section

Articles

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