Project Details

• The Business Insights 360 dashboard provides a unified analytical view across Finance, Sales, Marketing, and Supply Chain for AtliQ Hardwares. The solution was designed to replace static Excel-based reporting with an interactive, real-time business intelligence platform.

• Data from multiple sources was cleaned, transformed, and modeled using Power Query and Power BI, resulting in a structured data model with 10+ interconnected tables. Advanced DAX measures were implemented to calculate time intelligence metrics, financial KPIs, and performance indicators.

• The dashboard includes department-wise KPI views, drill-through navigation, and interactive filters to support detailed analysis at multiple levels. The layout was optimized for both operational teams and leadership to enable faster, insight-driven decision-making.

• This project strengthened my skills in Power BI, data modeling, DAX, and business-focused data storytelling.

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• This project was developed as part of a real-world pilot analytics engagement for Shield Insurance during the Codebasics Virtual Internship. The objective was to transform raw insurance transaction data into actionable business insights using Power BI.

• A structured data model was designed using fact and dimension tables, supported by Power Query transformations. Advanced DAX measures were implemented to calculate revenue, customer growth, month-over-month performance, and settlement-related metrics.

• The dashboard includes multiple analytical views such as Executive Overview, Sales Mode Analysis, and Age Group Analysis, enabling stakeholders to filter data by city, month, policy, and sales channel.

• This project closely follows stakeholder requirements, client mockups, and documentation standards, simulating an end-to-end business intelligence workflow used in professional analytics teams.

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• This project was developed as a business analytics case study to evaluate the impact of the 5G launch on Wavecon Telecom’s performance. The objective was to assess changes in revenue, customer behavior, market share, and plan performance before and after the introduction of 5G services.

• The Power BI dashboard tracks executive KPIs such as Total Revenue, ARPU, Active Users, and Unsubscribed Users, supported by detailed city-level and plan-level analysis. Data was modeled and transformed using Power Query and Excel, with optimized DAX measures enabling time-based comparison and performance tracking.

• Interactive visuals allow stakeholders to compare pre-5G and post-5G performance, identify underperforming KPIs, and evaluate which plans benefited most from the 5G rollout.

• This project highlights my ability to deliver business-focused insights through data storytelling, executive dashboards, and stakeholder-oriented reporting.

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• The Hotel Sales Performance Dashboard is a Power BI solution developed to analyze and monitor hotel performance across multiple cities. The dashboard tracks key hospitality metrics including bookings, revenue, occupancy rate, cancellations, and customer ratings using data from five interconnected tables.

• Data was cleaned, transformed, and modeled using Power Query and Power BI to create a structured and reliable analytical model. DAX measures were implemented to calculate performance KPIs and trend indicators.

• Interactive visuals, slicers, and drill-down functionality enable hotel management to compare performance by city, time period, and room category. The dashboard helps identify underperforming properties, monitor occupancy patterns, and evaluate customer satisfaction trends.

• This project strengthened my skills in ETL, data modeling, DAX, and hospitality-focused business intelligence reporting.

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• This project focuses on analyzing financial performance by developing Profit & Loss (P&L) reports across fiscal years, months, and markets, along with quarterly Gross Margin (GM%) analysis.

• Data was cleaned, transformed, and modeled using Excel Power Query and Power Pivot to create a structured financial data model. DAX-based calculated measures and time intelligence were implemented to support trend analysis and performance comparison.

• Interactive dashboards were designed to enable stakeholders to monitor revenue, costs, profitability, and margin trends at multiple levels. The reports support financial review, forecasting analysis, and data-driven decision-making.

• This project strengthened my understanding of financial analytics, Excel-based BI reporting, and presenting financial insights in a clear, management-ready format.

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• This project focuses on analyzing sales and customer performance to generate actionable business insights. Customer behavior, product sales, and market performance were evaluated against defined targets to identify growth opportunities and performance gaps.

• Data was cleaned, transformed, and modeled using Excel Power Query and Power Pivot to create a structured analytical model. DAX-based calculations were used to track KPIs related to revenue, customer contribution, and product performance.

• Interactive dashboards and reports were designed to enable analysis by customer segment, product category, and market. The insights support data-driven sales strategy optimization, customer segmentation, and performance monitoring.

• This project demonstrates my ability to use Excel as a BI tool for sales analytics, KPI tracking, and management-ready reporting.

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• This project focuses on analyzing hospitality datasets related to bookings, hotels, room categories, and date dimensions using Python. Data was cleaned and processed using Pandas and NumPy, followed by exploratory data analysis to understand booking behavior, occupancy patterns, cancellations, and revenue trends.

• Multiple Jupyter notebooks were created to explore seasonal trends, city-level performance, high-demand room categories, and customer booking preferences. Visualizations using Matplotlib and Seaborn were used to support trend identification and comparative analysis.

• The analysis highlights opportunities for revenue optimization, improved occupancy management, and better understanding of customer behavior across booking platforms and locations.

• This project demonstrates my ability to apply Python for structured data analysis, EDA, and insight generation in a real-world business context.

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