Client Background

Client: A Leading Real Estate Firm in the USA

Industry Type: Real Estate

Services: Land, Infrastructure, Real Estate, Investment

Organization Size: 100+

Project Description

The client’s own raw database needed to be converted into a dynamic web application with modern features like user management and subscription where users could explore land records as per their wish.

Our Solution

Created the web application as per client needs.

Added user functionality to handle signup/logins and added authorization middlewares to protect routes from unwanted access.

Transformed raw data into a meaningful NoSQL-based database with a proper schema being served as an instance on a cloud service named 

‘ MongoDB Atlas ‘.

Project Deliverables

Pushed code to the required GitHub repository.

Tools used

– Vanilla javascript

– Javascript Frameworks ( Nodejs, express , cors )

– Postman

Language/techniques used

– JavsScript

– Backend Service setup ( express, cors , js )

– Fronted logic setup ( HTML , CSS , JavaScript , Jquery )

Models used

Backend: An API service created to handle land records database and queries made by users.

Frontend: A frontend client is available as a web application where users can signup and access land records. 

Skills used

JavaScript Programming, APIs, JavaScript Frameworks ( NodeJS, Express  , cors ) , Web Design, NoSQL querying in MongoDB.

Databases used

MongoDB (NoSQL)

Web Cloud Servers used

MongoDB Atlas

What are the technical Challenges Faced during Project Execution

– UI component creation

– User authorization middleware creation

– Querying data in NoSQL

How the Technical Challenges were Solved

– Created and extended UI components to handle filters like owners, date fields, and area ranges on land records.

– API and Frontend are separately built for easier team management of tasks.

– Using a cloud-based MongoDB instance provided support for teams to work without any problems with accessibility.

Business Impact

– Created a platform for clients’ business.

– Transformed his raw data into meaningful business applications.