Project Details

AirPure Innovations, a consumer appliances startup, wanted to validate whether there was a strong and sustained demand for air purifiers in India before investing in R&D. The key business questions were:

Which pollutants should the purifier target?

What features do consumers expect?

Which cities show the highest demand and market size?

How can R&D align with local pollution patterns?

To answer these, I analyzed 3+ years of AQI data across diffrant cities, mapped pollutants region-wise, studied health impact correlations, tracked consumer awareness through Google Trends, and reviewed competitor strategies.

What I learned: I gained hands-on experience in connecting real-world business problems with data analytics. This project taught me how to transform raw datasets into actionable insights that reduce uncertainty and guide strategic decisions. It also enhanced my skills in Power BI, data storytelling, and market research analytics.

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Project Details

Project Details
In this project, the goal is to be one report which could be used by stakeholders from sales, marketing, finance and executive team. The focus is made on the following

1. Robust Data Modeling
2. User-empathetic Report design
3. Drillable Insights

I learned the following things in this project

1. Power Query (Basic and Advanced Operations)
2. Basic and complex DAX formulas
3. Data modelling involving 10+ tables
4. Choosing the right visuals and formatting
5. Dashboard designing principles
6. Using bookmarks
7. Deploying in Power BI service
8. Stakeholder Feedback Implementation
9. Sales, Marketing, Finance & Supply Chain metrics

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Project Details

In this project, I created a sales report using excel pivot tables which will enable businesses to determine effective customer discounts, facilitate negotiations with consumers, and identify potential business expansion opportunities in promising countries. The reports generated will provide actionable insights and recommendations for businesses to optimize their sales strategies, enhance customer satisfaction, and maximize revenue generation.

I have learned the following:

1. Pivot table
2. Power Query
3. DAX (Basics)
4. Conditional Formatting
5. Report Beautification
6. Sales Domain Metrics

Overall, this project aims to empower businesses with the necessary tools and insights to monitor, evaluate, and enhance their sales activities. By leveraging sales data analysis, businesses can unlock new opportunities, drive growth, and stay competitive in the dynamic market landscape.

Project Details

This project showcases SQL skills for data analysts by exploring, cleaning, and analyzing retail sales data. The goal was to answer key business questions through ad-hoc SQL queries and provide actionable insights.
Objectives:

Build and populate a retail sales database
Clean data by removing missing/null records
Perform EDA to understand sales patterns, customer behavior, and product categories
Analyze sales trends, top customers, high-value transactions, and category performance

Key Findings:

Identified top-selling months and high-value transactions
Analyzed customer demographics and category popularity across age groups
Evaluated performance by shifts (Morning, Afternoon, Evening)
Calculated average sales per category and derived gender-based purchasing insights

Skills Demonstrated:
SQL querying (SELECT, JOIN, GROUP BY, RANK, CASE), CTEs, window functions, ad-hoc analysis, data cleaning, exploratory data analysis, trend analysis, and sales performance evaluation.