This project is a complete end-to-end data exploration and visualization journey using a synthetic beauty products dataset (15,000 rows) from Kaggle. I combined SQL querying with Excel dashboarding to analyze trends, derive insights, and strengthen hands-on data skills — all from scratch, without any YouTube or external help.
Source: Kaggle - Synthetic Beauty Products Dataset
❗This dataset is 100% synthetic and intended for learning purposes only.
Key Fields:
- Product Names, Brands, Categories
- Price (in USD)
- Ratings (out of 5)
- Number of Reviews
- Usage Frequency (Daily / Weekly / Monthly)
- SQL: For querying, KPIs, and insights
- Excel: For dashboard creation using:
- Pivot Tables
- Pivot Charts
- Slicers (partial implementation due to version limitations)
- Thematic formatting for better storytelling
- Explore beauty product trends across 40 synthetic brands.
- Derive actionable KPIs and insights from product price, rating, review, and frequency.
- Strengthen SQL query structuring from scratch without tutorials.
- Build an aesthetic yet minimal Excel dashboard aligned with industry visuals.
Over 20+ SQL queries were written, focusing on:
- Top rated brands and products
- Product pricing ranges per brand
- Average rating per category
- Most reviewed products
- Most frequently used product types
- Price-to-rating ratio insights
🗒 All queries and insight notes are available in the PDF file.