Data Analytics and Reporting API – A Reliable Tool for Data Visualization and Predictive Analysis


  • Joe Louis Paul Ignatius Associate Professor, Department of Information Technology, Sri Sivasubramaniya Nadar College of Engineering, Rajiv Gandhi Salai (OMR), Kalavakkam-603 110, Chennai, Tamil Nadu, India.
  • Sasirekha Selvakumar Sri Sivasubramaniya Nadar College of Engineering
  • Spandana JSN Sri Sivasubramaniya Nadar College of Engineering
  • Subasri Govindarajan Sri Sivasubramaniya Nadar College of Engineering



DARAPI, data analytics, feature engineering, machine learning, reporting API


Data analytics, the science of analyzing raw data is widely being used in a broad range of applications to make
effective, efficient and timely decisions in the real-time prediction problems. Analytics requires the user to have
an in-depth knowledge about the various steps involved in the process for arriving at the conclusions. Hence, to
make it easier for the naïve users, Data Analytics and Reporting API (DARAPI) provides Analytics as a Service in
the form of an Application Programming Interface (API) has been proposed. DARAPI is aimed to ease the process
of analyzing the data by the users without requiring their expertise in the field. It accepts the input file from the
user and performs pre-processing techniques at various stages including imputation of missing data, detection
and replacement of outliers, encoding of categorical variables, and etc. Furthermore, feature engineering is performed, based on which DARAPI will execute the different classification/regression models and finally delivers
the model which provides the best accuracy for future predictions. This entire system is rendered to the user in
the form of an API that can be called from any device that is Internet enabled. DARAPI stands unique with its embedded feedback mechanism which generates constructive input for future predictions. This feature enhances
the performance of the system in comparison with the existing tools. DARAPI proves beneficial not only to the
naïve users but also to the experts by saving their time and efforts needed in understanding the data.