| File Name | Description |
|---|---|
Digital_Sales_Unique.csv |
Cleaned dataset used to build the dashboard |
Task 8.pbix |
Power BI project file with all visualizations |
TASK_8_DA.pdf |
Internship task description for Task 8 |
Interactive Digital Sales Dashboard.pdf |
Well-written insights extracted from the dashboard made using canva |
README.md |
Overview and documentation of the project +Interview Q/A |
To help stakeholders and business teams understand digital product sales performance, identify best-selling products, and track trends across time, region, and category.
Created as part of the data analyst internship project, this interactive Power BI dashboard provides a comprehensive overview of digital product sales, customer trends, and category-wise performance.
-
Top Products:
E-book: AI for Beginners and Budget Tracker Tool led with the highest revenue—highlighting demand for self-learning and personal finance tools. -
Sales Peak:
May 2024 recorded the highest monthly sales (₹1492), with a gradual decline—potentially seasonal trends or campaign impact. -
Regional Performance:
The UK and Canada were the top-performing regions, each generating more than ₹2200. -
Category Trends:
Health & Wellness, Productivity, and Finance categories dominated, indicating a preference toward personal growth and productivity.
This project helps analyze and understand digital product sales across:
- 📅 Different months
- 🌍 Regions
- 🗂️ Categories
- 🛒 Products
It enables users to:
- Monitor key sales trends
- Identify best-performing products and categories
- Compare region-wise performance
- Explore insights interactively using slicers and filters
- Removed nulls and duplicates
- Converted columns to proper data types
- Standardized date formats
- Ensured consistency in product and category naming
Line chart showing monthly sales from May 2024 to Apr 2025, identifying peak and low-performing months.
Bar chart comparing revenue across countries like the UK, Canada, India, USA, and Australia.
Donut chart showing contributions of categories like Health & Wellness, Productivity, Finance, and Education.
Table highlighting digital products with the highest sales and profits.
Region and category slicers allow users to drill down and analyze performance by geography and segment.
- Power BI Desktop
- Excel/CSV for Data Handling
- DAX for minor calculations
- Basic Data Cleaning (Date, Nulls, Types)
- Clone this repository or download files.
- Open
Task 8.pbixin Power BI Desktop. - Use the slicers and visual elements to explore the data.
- Review the insights and interview answers in the supporting documents.
Interview Questions & Answers
- What does a dashboard do?
A dashboard visually summarizes key data metrics in one place, helping users quickly understand patterns, trends, and insights. My dashboard highlights sales performance across products, regions, and categories to support business decisions.
- How do you choose the right chart?
The chart type depends on the data: • I used a line chart for monthly sales to show trends over time. • A bar chart to compare sales across regions. • A donut chart for category-wise sales distribution. This ensures clarity and makes patterns easier to spot.
- What is a slicer/filter?
A slicer is an interactive tool that allows users to filter data based on specific fields. In my dashboard, I used a Region slicer so users can view how different areas performed individually.
- Why do we use KPIs?
KPIs (Key Performance Indicators) help track progress toward business goals. Although I didn’t include a specific KPI card, the visuals show top-performing products, peak sales months, and regional contributions, which act as performance indicators.
- What did your dashboard show about sales?
It showed that: • E-books and budgeting tools were the top-selling products. • December 2024 had the highest sales, followed by a steady decline. • UK and Canada led in regional sales. • Health & Wellness and Productivity were the most profitable categories.
- How do you make a dashboard look clean?
I used: • Consistent colors and fonts • Minimal visual clutter • Proper titles and labels • Balanced layout of charts and slicers This helps users focus on insights, not just visuals.
- Did you clean the data before starting?
Yes. I ensured: • Dates were in the right format • Nulls or duplicates were removed • Sales and profit fields were numeric This prepared the data for accurate analysis and visualization.
Feel free to fork the repo, open issues, or suggest improvements to enhance this dashboard further.
📎 [Connect on LinkedIn]https://www.linkedin.com/posts/activity-7321086708593168384-MVL5?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAADazOB0BRuax1fAhu4L7QyodlFZtYz-UgyU