This project is a Flask application that provides a dashboard for tracking medicine and wellness sales data. It is connected to a MongoDB database and utilizes Grafana for data visualization.
To run the application, follow these steps:
- Clone the repository:
git clone https://github.com/aliziauddin/Pharma-Data-Analytics.git- Navigate to the app directory:
cd Pharma-Data-Analytics/app- Start the application using Docker Compose:
docker-compose upThis command will start the Flask app along with the MongoDB database. It will launch three instances of the app, one for each container 🐳.
- Access the application:
Once the containers are up and running, you can access the application by navigating to
http://localhost:3000in your web browser.
-
Sales Dashboard: The app provides a graphical dashboard to visualize medicine and wellness sales data. It uses Grafana for data visualization, allowing you to create interactive charts and graphs 📊📈.
-
MongoDB Integration: The application is connected to a MongoDB database to store and retrieve sales data. It uses an ORM (Object-Relational Mapping) library, such as PyMongo or MongoEngine, to interact with the database 📁💾.
-
Dockerized Environment: The entire application, including the Flask app and MongoDB, is containerized using Docker. This ensures consistent and reproducible deployments across different environments 🐳🚀.
-
Data Collection: The application collects sales data from various sources, such as point-of-sale systems or online platforms. You can configure the data collection process to import data automatically or manually upload data files 📊📥.
-
Database Configuration: The connection details for the MongoDB database can be configured in the
server.pyfile. Update theMONGO_URIvariable with the appropriate MongoDB connection string ⚙️🔧. -
Grafana Integration: Grafana is configured to connect to the MongoDB database and retrieve sales data for visualization. You may need to configure the data source settings in Grafana to point to the correct MongoDB instance 📈🔌.