Materialized View Generation Using Apriori Algorithm

Data analysis is an important issue in business world in many respects. Different business organizations have data scientists, knowledge workers to analyze the business patterns and the customer behavior. Scrutinizing the past data to predict the future result has many aspects and understanding the nature of the query is one of them. Business analysts try to do this from a big data set which may be stored in the form of data warehouse. In this context, analysis of historical data has become a subject of interest. Regarding this, different techniques are being developed to study the pattern of customer behavior. Materialized view is a database object which can be extensively used in data analysis. Different approaches are there to generate optimum materialized view. This paper proposes an algorithm which generates a materialized view by considering the frequencies of the attributes taken from a database with the help of Apriori algorithm.