Volume 16, Number 6

Unveiling Patterns: Advanced Data Mining Techniques for Accurate Predictive Analytics

  Authors

Sumi Akter and K M Yaqub Ali, Washington University of Science & Technology (WUST), USA

  Abstract

With the rapid increase in the volume, variety and availability of data across organizations, managers are confronted with the task of analyzing data for meaningful information. As today’s undeniable evidence shows, data mining imperatives and its close cousin predictive analytics have become fundamental recognized approaches of operationalizing raw data into strategic decision supports. Data warehousing and data mining are two distinct ideas. Predictive analysis is the process of applying the extracted data model to anticipate possible future events, while data mining is the process of uncovering the hidden facts and model of a massive data pile. Learn more about a variety of specialized data mining techniques that improve the effectiveness of predictive analytics by refining aggregation, decision trees, neural networks, support vector machines, and association rule mining by reading this article.

  Keywords

Data mining, Predictive analytics, Advanced data mining techniques, Machine learning, Artificial intelligence, Clustering, Decision trees, Neural networks, Support vector machines, Association rule mining, Data quality, Ethical considerations, Forecasting, Real-time decision-making, Healthcare predictive analytics, Retail predictive analytics, Data privacy.