V3I5P154

Predictive Analytics in Business Intelligence

Ankit Choudhari^1*, Neha Tiwari², Himanshu Ranjan³

Abstract

Predictive Analytics for Business Intelligence (BI) has come up as a revolutionary strategy that will benefit all those businesses which want their decisions based on facts. By applying the combination of statistical methods, machine learning, data mining, and artificial intelligence in their current BI strategy, firms can predict future trends, actions of consumers, possible risks, and demands of the market with more precision. In this research paper, an effort is made to explore how predictive analytics can be used within business intelligence strategies. The study highlights the benefits of using predictive models in improving organizational efficiency, effective allocation of resources, enhanced management of customers’ relationships, and strategic planning. In addition, the paper focuses on the system architectures, methods, and tools used in developing predictive BI systems. These include the use of data warehouses, big data technologies, and cloud computing. The challenges involved in using predictive analytics in businesses are also explored. The results show that companies employing predictive analytics in their business intelligence systems are able to make predictions and improve their decision making processes. Consequently, there is improvement in organizational performance. It is concluded that predictive analytics form an important part of business intelligence systems, which will play an important role in shaping the future of enterprise management [3].

Keywords:

Predictive Analytics, Business Intelligence, Machine Learning, Data Mining, Artificial Intelligence, Forecasting, Big Data, Decision Support Systems, Data Warehousing, Business Forecasting.