Paper Title
Business Analytics and Data mining techniques using Predictive Algorithms to enhance Business Intelligence

The objective of this paper is to present a review literature on what are impacts of Data Mining (DM) and Business Analytics (BA) in enhancing Business Intelligence (BI). The paper highlights various features of DM and BA using predictive algorithms. It includes three variants: explorations, pattern identification and deployment. Business analytics presents itself as an information system that combines different data from internal and external sources from organizations in order to help to improve the knowledge of the managers, as well as the decision-making process. The competitive advantage is created by better and greater understanding of the data. It focuses on business and gathers three types of analysis: descriptive, predictive and prescriptive. Data Mining is understood as one of the computing processes of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Business Intelligence is the hot topic among all industries aiming for relevance. BI emphasizes on detail integration and organizing of data. DM and BA work together to process and analyze data to lighten workload for the user and organization and hence in understanding discovered materials. Predictive algorithm hence plays extensive role in enhancing BI. Keywords - Business Intelligence, Data Mining, Data Analysis, Predictive Algorithms, Predictive Modelling, Business Operations Management