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 needs not to be well defined prior to the creation hence adding to its flexibility. MongoDB has lots of extensive built-in-features and is highly compatible with other software systems, with extensive ways of accessing data beyond JSON query, its highly compatible Business Intelligence Connector is highly compatible which makes it compatible. High scalability is making it remarkable and popular and hence made us think about writing a paper demonstrating the data conversion. This conversion has helped us in making the most of modern data. Data was stored on the cloud as cloud-based storage is an excellent and most cost-effective solution. Our 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 we have used is location based in MongoDB that can directly yield data without hitches which made us work on MongoDB with the focus on the latest feature of MongoDB to support Multi-Document ACID transactions to maintain data integrity.