Abstract

MongoDB is a document-oriented database which helps us group data more logically. This paper demonstrates the conversion of data from a native tabular form to unstructured documents. The document and collections within it needs not to be well defined prior to the creation of unstructured data in MongoDB. The MongoDB has lots of extensive built-in-features and is highly compatible with other software systems, with extensive and flexible ways of accessing data beyond JSON query, its highly compatible Business Intelligence Connector is highly compatible which makes it compatible with existing databases. High scalability is making it remarkable and popular in the World and hence made me think about writing a paper demonstrating the data conversion. This conversion has helped me in making the most of modern data to be compatible with MongoDB. Data is stored on the cloud as cloud-based storage is an excellent and most cost-effective solution. My solution is highly scalable as the built-in shading solution for data handling makes it one of the best big data handling tool. The data that i have used, is location based in MongoDB that can directly yeild document ACID transactions to maintain data integrity.