Portfolio - Ritwik Polasa

Python Project

Exploratory Data Analytics in Hospitality Domain

Domain/Function: Hospitality domain

Performed exploratory analysis on hotel booking data using Python to identify revenue patterns, occupancy trends, and platform performance. Generated insights that support pricing optimization and improved revenue management decisions for hospitality operations.

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Jupyter Notebook

Exploratory Data Analytics in Hospitality Domain

Visualization of booking platform distribution with a horizontal bar chart and descriptive statistics for key booking and revenue metrics.

Showing hotel-wise revenue aggregation, average city ratings, and booking platform analysis using Pandas groupby and summary tables.

Project Details

Conducted Exploratory Data Analysis for AtliQ Grands, a luxury hotel chain, to understand revenue and occupancy patterns. Used Python with Pandas and NumPy for data cleaning and transformation, including removal of invalid guest records and revenue outliers. Created occupancy metrics and analyzed revenue by hotel type, city ratings, and booking platforms.

Visualizations revealed that luxury properties generated higher revenue but had inconsistent occupancy. Third-party platforms contributed most bookings, indicating commission dependency. City-level analysis showed demand concentration in major markets with growth potential in others.

The analysis supported recommendations such as dynamic pricing, reduced platform dependency, and demand-based expansion planning to improve revenue performance.

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Excel Project

AtliQ Hardwares Sales & Analysis

Domain/Function: Retail/Manufacturing Analytics

Analyzed multi-year sales and financial data using Excel and Power Query to identify product, market, and retailer performance. Built dashboards that helped evaluate growth trends, profitability, and business gaps for strategic decision-making.

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Microsoft Excel

Customer net sales performance dashboard for India (2019–2021) showing customer-wise growth, 2021 vs 2020 comparison, and visual data bars for quick trend assessment.

AtliQ Hardwares market performance vs target by country (2019–2021) with conditional formatting highlighting 2021 gaps to target in value and percentage.

Project Details

Performed financial and sales analysis for AtliQ Hardwares using Microsoft Excel. Cleaned and transformed multi-year sales data with Power Query and developed interactive Pivot Table dashboards.

Analyzed year-over-year sales growth, product performance, country-level trends, retailer contribution, and gross margins. Identified key revenue drivers and profitability variations across markets and products.

The study showed strong revenue growth with uneven profitability across regions. Top products and retailers were identified along with underperforming markets.

Insights supported decisions such as prioritizing high-margin products, improving retailer strategies, and addressing performance gaps across markets.

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PowerBI Project

Business Insights 360

Domain/Function: Retail/Manufacturing Analytics

Developed an end-to-end Power BI dashboard analyzing financial, sales, and supply chain performance. Identified profit leakages, forecast issues, and margin pressures, enabling data-driven decisions to improve business profitability.

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Finance view of P&L and net sales performance view with monthly bar chart, top/bottom customers and segments, and detailed profit and loss statement KPIs.

Executive view summarizing global net sales, margins, net profit, regional KPIs, and customer/product performance with interactive filters.

Project Details

Built an end-to-end business intelligence solution for AtliQ Hardwares using Microsoft Power BI. Integrated financial, sales, marketing, and supply chain datasets using Power Query and created KPI measures with DAX.

Developed dashboards analyzing revenue growth, gross margins, net profit, market performance, customer contribution, and forecast accuracy.

Analysis revealed that revenue growth did not translate into proportional profit due to margin pressure and operational costs. High-volume customers generated large sales but lower profitability. Forecast instability caused excess inventory and stockouts.

The solution improved visibility into profitability drivers and supported strategic decisions on pricing, forecasting, and market strategy.

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Ritwik Polasa

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Exploratory Data Analytics in Hospitality Domain

AtliQ Hardwares Sales & Analysis

Business Insights 360

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Ritwik Polasa

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