Prediction and Retrieval of Information in Big Data Technology with Data Warehouse

Abstract

The big data technology with the data warehouse provide better public services analytics and it can help governments make quicker and more effective policy, investment and infrastructure decisions. The data warehousing and the big data is a storehouse of land record information. The need for storing and retrieving land record data is increasing progressively due to population growth, education, political analytics etc. In order to manage these kinds of information, Government need to use efficient and large database for storage purposes and retrieve correct informations. Besides, the problems may occur due to some challenges while retrieving a person’s details from the large data sets. Also maintenance of enormous quantity of data is not a simple task. In order to eliminate such limitations, we proposes a novel Fuzzy-Cat Swarm Optimization (FCSO) method to analyse, store and retrieve the land record information accurately. This proposed method consist of, Artificial Neural Network (ANN) that classifies the input land record data for organizing the information as different classes in the database. Then, the proposed method uses a mongo database to store large amount of land record information. Moreover, it provide easy maintainece of data, updating of land records and security of the system. Besides, the FCSO approach is used to attain the accurate retrieval results for user’s queries. Thus, the users can access their records easily by means of fuzzy optimized approach. Therefore, the land record data maintenance and decision making for retrieving information can be easily and efficiently processed using this proposed system. Finally, the performance of the proposed method is evaluated for the land record information retrieval results.