Enterprise Sales Monitoring

Project Overview

An enterprise solution designed for high-level sales-performance tracking. The platform integrates different data sources of different subsidiaries into a single platform, with interactive geographical data visualization, order tracking, and dedicated customer behavior analysis. It is designed to enable decision-makers to monitor performance metrics across different companies.

Demo Access:

Click on the Image to visit the live application.

The Demo is run with synthetic but realistic data.

System Architecture

The system architecture is designed to be connected directly to the customer's ERP system in read-only mode, allowing for real-time data synchronization and analysis. This is achieved through the use of API endpoints that are exposed by the cloud-based ERP system and accessed by the data pipeline triggered by the user directly from the webapp.

The application is built on a serverless architecture using Next.js for both the frontend and API layers. Data is ingested through serverless functions, processed via API routes, and stored in a NoSQL database to ensure low-latency access and scalability. The frontend visualizes this data through interactive dashboards and geospatial maps. The webapp is hosted on Vercel but can be easily deployed on any other platform through CI/CD pipelines and containerization. Take a look at the Demo above with unlimited access.

Data Pipeline

Whenever the pipeline is triggered, an Azure Function is invoked to provision a Python-based processing resource. This resource retrieves data from the ERP system, compares it with previously processed records to identify new entries, and updates the Storage Account accordingly. Finally, the processed data is loaded from the Storage Account into Azure Cosmos DB.

This configuration allows for lower costs through the storage account that stores all the data while the data is being processed, while the lower latency database (cosmos db) is used to store the processed data for faster access and analysis.