  Ever since the era of internet had ushered in cloud computing, there had been
increase in the demand for the unlimited data available through cloud computing
for data analysis, pattern recognition and technology advancement. With this
also bring the problem of scalability, efficiency and security threat. This
research paper focuses on how data can be dynamically mine in real time for
pattern detection in a secure cloud computing environment using combination of
decision tree algorithm and Random Forest over a restful Application
Programming Interface (API). We are able to successfully Implement data mining
on cloud computing bypassing or avoiding direct interaction with data warehouse
and without any terminal involve by using combination of IBM Cloud storage
facility, Amazing Web Service, Application Programming Interface and Window
service along with a decision tree and Random Forest algorithm for our
classifier. We were able to successfully bypass direct connection with the data
warehouse and cloud terminal with 94% accuracy in our model.
