Data dashboard case study
Positive Grid Spark Sales Dashboard
A data dashboard tracking Positive Grid Spark amplifier preorder volume and estimated revenue.
This project started as a lightweight Python Dash app for monitoring public preorder metrics for the Positive Grid Spark amplifier. It combined a small data pipeline with an interactive Plotly dashboard to make the sales trend easier to inspect.
The app read a Google Sheet through a service-account credential, loaded the sales_totals worksheet, converted the counter fields into numeric values, and grouped observations by date. The dashboard then plotted daily totals and estimated sales revenue as an area chart.
It is a compact example of a useful analytics pattern: collect a product signal, preserve the historical readings, and build a focused interface for understanding demand over time. The version below keeps the same dataset visible with a modern interactive chart.
This is the same pattern I like in larger decision tools: collect a signal, preserve history, model the shape of the problem, and make the result easy to inspect.