Recommendation system for financial analytics

Due to advancement in Science and Technologies there are enormous amount of data available on internet. A large amount of structured, semi-structured and unstructured data is being created at a very rapid speed every day from heterogeneous sources like reviews, ratings, feedbacks, shopping details, etc., it is termed as Big Data. This data generated from different users share many common patterns which can be filtered and analysed to give some recommendation regarding the product, goods or services in which a user is interested. Recommendation systems are the software tools used to give suggestions to users on the basis of their requirements. Many people are not so much aware of different profitable and economical alternatives before using their money for goods or services. They are not so intelligent that they can quickly compare and judge that which product or service is better. The presented paper proposed a recommended system for management and utilisation of three components of salary i.e. saving, investment and expenditure. Many savings and investment consulting systems are available but no system provides effective and efficient recommendation regarding management and beneficial utilisation of salary. The advantage of proposed recommended system is that it provides better suggestion to a person for saving, expenditure and investment of their salary which in turns maximises their wealth. Due to enormous amount of data involved, Apache Hadoop framework is used for distributed processing. Apache Mahout is used for analysing the data and implementation of the recommender system.