Project Details

In this project, I developed a sales report using Excel Pivot Tables to help businesses understand their sales performance better. This report is a powerful tool for identifying the best customer discounts, making negotiations easier, and finding new markets to explore.

The insights from these reports can help businesses improve their sales strategies, boost customer satisfaction, and increase revenue.

During this project, I learned how to:

1. Use Pivot Tables for quick data analysis.
2. Apply Power Query for smooth data processing.
3. Understand the basics of DAX (Data Analysis Expressions).
4. Use Conditional Formatting to highlight important information.
5. Make reports visually appealing and easy to read.
6. Analyze key sales metrics effectively.

Overall, this project gives businesses the insights they need to enhance their sales efforts and discover new growth opportunities through data analysis.

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

Live Interactive Dashboard

Project Details

Performed analysis of hotel revenue data to assess financial performance and identify key trends. The project involves collecting data on room rates, bookings, occupancy, and total revenue. Created several Dax measures for calculating average daily rate (ADR), revenue per available room (RevPAR), occupancy percentage, and several other key metrices to evaluate the hotel's profitability and operational efficiency. The goal was to provide data-driven insights into seasonal trends, peak booking periods, and strategies to improve revenue management for the hotel industry.

Key learnings:

- Created over 15+ DAX measures to compute key financial metrics like ADR, RevPAR, occupancy rate etc.
- Seasonal and Trend Analysis of revenue
- Profitability & Operational Efficiency Insights
- Dashboard Design & Visualization:

Live Interactive Dashboard

Project Details

Atliqo’s business director requested their analytics team to provide a comparison report of KPIs between pre and post-periods of the 5G launch. The management is keen to compare the performance between these periods and get insights which would enable them to make informed decisions to recover their active user rate and other key metrics. They also wonder if they can optimize their internet plans to get more active users. Peter Pandey, a junior data analyst is assigned to this task.

Task: Imagine yourself as Peter Pandey and perform the following task

Create the comparison report based on the mock-up provided. Please note the mock-up is created by a business user who has a minimal idea about dashboarding. Hence you need to represent the insights

Live Interactive Dashboard

Project Details

𝐀𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐂𝐨𝐦𝐩𝐚𝐧𝐲: AtliQ Hardware excels in the computer hardware sector, serving both domestic and international markets.

𝐓𝐡𝐞 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: Responding to the need for data-driven decisions, AtliQ Hardware's management initiated a SQL challenge to strengthen their analytics team. My task was to interpret 10 ad-hoc SQL requests and transform them into actionable insights.

𝐊𝐞𝐲 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐚𝐧𝐝 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬:

📌𝐌𝐚𝐬𝐭𝐞𝐫𝐞𝐝 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭𝐚𝐭𝐢𝐨𝐧: Emphasized thorough understanding of data before delving into SQL queries.

📌𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐒𝐐𝐋 𝐒𝐤𝐢𝐥𝐥𝐬: Explored advanced concepts like Common Table Expressions (CTE), JOIN operations, Stored Procedures, etc.

📌𝐋𝐢𝐧𝐤𝐞𝐝 𝐒𝐐𝐋 𝐭𝐨 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: Demonstrated practical applications of SQL in business contexts, beyond mere skill.

Project Details

This project is a deep dive into consumer credit card usage behavior in India, performed using ad hoc SQL analysis. The goal was to simulate real-world business queries that companies might raise to understand user behavior, market segmentation, product impact, or campaign effectiveness.

I sourced the dataset from Kaggle, which contains anonymized records of credit card transactions across multiple Indian cities. Using SQL, I answered nine business-driven questions covering transaction patterns, spend growth, popular cities, customer segmentation, and more.

This project showcases how structured thinking + SQL querying can help derive quick and valuable insights from raw data, especially in time-bound or on-demand reporting scenarios like dashboards or executive requests.