Datalyser

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  Hover on total loss, extra money that the company could have made if it didn't have to turn down people

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  Hover on total revenue

Inspiration

The need for efficient scheduling and financial tracking in busy service industries, like tire shops, inspired us to develop Datalyser.

What it does

Datalyser optimizes schedules, calculates actual and potential earnings, and identifies lost revenue opportunities from a CSV file.

How we built it

We used Python and its data manipulation libraries for the backend, coupled with a user-friendly frontend interface made with React.js for easy operation.

Challenges we ran into

Specific problems regarding data manipulation with the CSV file

Accomplishments that we're proud of

Successfully integrating complex backend algorithms with an intuitive interface and delivering real-time financial insights stands out for us.

What we learned

We gained valuable insights into time management, algorithmic scheduling, data processing, and balancing technical complexity with user experience.

What's next for Datalyser

We plan to enhance Datalyser with AI-driven predictive analytics for better forecasting and integration with broader business management tools.

Built With

• python
• react