Project Details

In this project, I've developed a dynamic sales report using Excel pivot tables, offering businesses invaluable insights into customer discounts, negotiation strategies, and untapped markets. These reports provide actionable recommendations, empowering businesses to refine sales tactics, elevate customer experiences, and maximize revenue.

Throughout this journey, I've honed skills in:

1. Pivot tables
2. Power Query
3. Basic DAX functions
4. Effective Conditional Formatting
5. Report Presentation
6. Sales Domain Metrics

The primary goal is to arm businesses with the tools and insights needed to monitor, assess, and optimize their sales efforts. By leveraging data-driven analysis, businesses can uncover opportunities for growth, adapt to market changes, and maintain a competitive edge in an ever-evolving landscape.

Project Details

Company: AtliQ Hardwares (an imaginary leading computer hardware producer in India with a global presence)

Challenge: AtliQ Hardwares aimed to enhance data-driven decision-making by expanding their analytics team. Tony Sharma, the Data Analytics Director, devised a SQL challenge to evaluate candidates' technical and soft skills.

My Task: As a hypothetical applicant, I:

Reviewed 'ad-hoc-requests.pdf' with 10 business queries.
Crafted and executed SQL queries.
Developed a Power BI and PowerPoint presentation to showcase insights to top management.

Approach: Utilized MySQL for data retrieval and analysis. Employed Power BI for impactful visualizations. Designed a professional presentation to communicate findings and recommendations effectively.

Outcome: This project demonstrated my ability to handle complex data queries and present findings effectively, enhancing both my technical and communication skills.

Project Details

As a data analyst at Goodcabs, I was tasked with assessing the company's performance across key metrics such as trip volume, passenger satisfaction, and repeat passenger rates. The project aimed to support the Chief of Operations in making strategic decisions to drive growth and enhance service in tier-2 cities.

I developed three key analytical views:

1. Business Overview – A high-level summary of performance metrics, including trip volume and satisfaction ratings, identifying patterns and areas for improvement.
2. City vs. Target Analysis – A city-specific comparison of actual performance against 2024 targets, revealing areas of success and cities needing more focus.
3. Repeat Passenger and Rating Analysis – An examination of repeat user behavior and satisfaction, offering insights into customer loyalty and retention strategies.

These analyses helped identify growth opportunities and optimized resource allocation for Goodcabs’ expansion in tier-2 cities.

Live Interactive Dashboard

Project Details

Throughout this project, I've honed my skills using tools like Pandas for effective data manipulation and analysis. Engaging with diverse datasets, I've gained expertise in:

Understanding Business Problem:🌍
AtliQ Grands faces declining market share and revenue. Analyzing data is crucial to support data-driven decisions.

Data Understanding:🔍
Familiarizing with the data and problem statement to plan effective analysis.

Data Collection:📂
Gathering necessary data to provide meaningful insights through analysis.

Data Cleaning:🧹
Rigorously checking for missing values, outliers, and errors to ensure data quality.

Data Transformation:🔄
Structuring cleaned data to uncover trends impacting business performance.

Insights Generation:💡
Uncovering hidden insights to guide strategic decisions for improving market position and revenue growth at AtliQ Grands.

Project Details

This project provides a comprehensive analysis of Shield Insurance’s data, presented across three key views:

➡️General view: Highlights major KPIs, customer and revenue trends, and customer segmentation by age and city.
➡️Sales Mode Analysis: Explores customer and revenue segmentation, along with monthly revenue trends across various sales modes.
➡️Age Mode Analysis: Delivers insights into customer segmentation, policy preferences, and monthly customer trends categorized by age groups.

The findings led to a 10% increase in active users and a 15% rise in profits.📈

Live Interactive Dashboard