📊 Sales Forecasting Drill (BI Practice Project)

---

Overview

This project demonstrates how to design a complete Business Intelligence workflow from synthetic data generation to visualization and forecasting.

I built a small web app that generates realistic sales datasets for Power BI practice and then used it to create an interactive dashboard highlighting sales trends, expenses, profits, and a 3-month moving average forecast.

Process

1. Data generation:
   Used my custom React + Vite app hosted on Vercel to produce synthetic monthly sales and expense data with controlled growth and random variation.
2. Data visualization:
   Imported the dataset into Power BI and created a dashboard combining bar charts, KPIs, and a 3-month moving average line to reveal underlying sales trends.
3. Forecasting logic:
   The “Sales Forecast” line applies a DAX formula calculating a rolling 3-month average of total sales — a simple way to visualize short-term momentum and identify trends.
4. Tools & stack:
   • App: React + TypeScript + Tailwind (deployed on Vercel)
   • Visualization: Power BI Desktop
   • Data scripting: Python (optional dataset generator)

Key Learnings

• Understanding of time-series modeling in BI context.
• Building reusable BI practice data tools.
• Applying DAX functions like DATESINPERIOD() and AVERAGEX() to smooth real-world metrics.
• Designing clear and actionable dashboards combining raw and trend-based data.

See it live

Outcome