Handling data analytics on unstructured data using MongoDB
Rajanikanth Aluvalu, M. A. Jabbar · 2018
Nowadays the amount of data generated from various device sources and business transactions is very huge. Most of the transactional, business data generated is unstructured. Business organizations use the data to perform analytics for decision making. Performing Analytics on such huge unstructured data has become a challenge for organizations. Enough tools and techniques both with free ware and proprietary license release are available to handle structured data. In earlier systems, unstructured data is converted into structured data and then stored in Database Management System (DBMS) for performing further analytics. This is a time consuming process. As the amount of data being generated is increasing tremendously, it has become impossible to transform huge amounts of data into structured data. In order to perform analytics of the digital data, we require different business processes to handle unstructured data directly and efficiently. Smart grid management and traffic congestion management requires handling unstructured data analytics. In this paper, a skillful mechanism is being proposed to handle unstructured data using MongoDB and perform required analytics. The experimental approach and the outcomes are presented.