Portfolio - Ashish Chauhan

Excel Project

Excel-Sales and Finance Analytics Project of AtliQ Hardwares

Domain/Function: Sales & Finance

The objective of this project is to offer in-depth analysis of the company's financial health and its standing in the market. It involves generating a range of reports such as "Customer Net Sales Performance" and "Market Performance vs. Target" using a combination of fundamental and advanced Excel.

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Excel-Sales and Finance Analytics Project of AtliQ Hardwares

The Customer Performance Report displays the yearly net sales performance for each customer.

This report allows stakeholders to evaluate the country's performance over multiple years and compare it to the established targets.

Project Details

In this project, I have created a sales report utilizing Excel pivot tables. This report serves as a valuable tool for businesses to determine optimal customer discounts, streamline negotiation processes, and identify opportunities for expanding into promising markets. The reports I've crafted offer actionable insights to assist businesses in enhancing their sales strategies, enhancing customer satisfaction, and increasing revenue.
Throughout this project, I have acquired expertise in the following areas:
1. Utilizing pivot tables
2. Harnessing the capabilities of Power Query
3. Grasping the fundamentals of DAX (Data Analysis Expressions)
4. Enhancing data presentation through conditional formatting
5. Improving the visual appeal of reports
6. Gaining insights into sales-related metrics
Overall, this project revolves around equipping businesses with the tools and knowledge necessary to enhance their sales efforts. By delving into sales data, businesses can uncover growth.

PowerBI Project

AtliQ- Business Insights--360

Domain/Function: Sales, Finance, Marketing & Supply Chain

AtliQ Hardware faced challenges managing data within Excel. Objective: Shift from Excel to Power BI for better comprehension. Goal: Achieve insights into finance, sales, and supply chain areas. Data Volume: 1.8 million entries. Tools Used: SQL, Power BI, Excel, DAX Studio.

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Designing a landing page that connects with users, making it an essential part of our dashboard.

Data Modelling involving 10+ tables

Project Details

This project, which combines Power BI, SQL, and Excel, centers around addressing operational issues at AtliQ Hardware, a prominent global consumer electronics company. The company's heavy reliance on Excel for data analysis has led to significant losses in some regions. To rectify this, senior management aims to initiate a data analytics project, leveraging data from the previous year to enhance performance and drive improvements.
💼Finance View: shows profit and loss statement like GM,NP,NS etc. and performance over time chart w.r.t to key metrices.
📣Sales View: Shows customers and product performance , unit economics and performance matrix by NS and GM%
📣 Marketing View: Shows region and product performance , unit economics and performance matrix by NS and GM%
🚚 Supply Chain View: shows forecast accuracy, Net Error, trends and key metrices by customers and product.
👨‍🎓 Executive View: shows market share of competitors, trends,revenue by division and channel, top 5 customer.

Project video

Live Interactive Dashboard

PowerBI Project

AtliQ Grand--Hospitality Analytics

Domain/Function: Hospitality

This project serves as a prime example of how data can bring about a significant transformation in the hospitality sector. It accomplishes this by delving into essential metrics like Revenue, ADR, RevPAR, Occupancy%, Realization%, Cancellation%, DBRN, DSRN, and more.

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Atliq Grands hotel chain classification

Designing a landing page that users connect with, making it a key part of our dashboard

Project Details

AtliQ Grands, renowned for its chain of five-star hotels across India, boasts a rich 20-year history in the hospitality sector. Nevertheless, they currently grapple with diminishing market share and revenue in the luxury and business hotel segment, attributed to competitive pressures and less effective management choices. In response to this challenge, the managing director of AtliQ Grands is embarking on a strategic initiative to integrate "Business and Data Intelligence" into their operations. The primary aim is to recapture market share and bolster revenue.
ACHIEVED OBJECTIVES
1. Formulated metrics in accordance with the provided metric list.
2. Designed a dashboard aligning with stakeholder-provided mock-up.
3. Generated valuable insights extending beyond the specified metric list and mock-up dashboard.
UTILIZED SKILLS
4. Leveraged Power BI
5. Employed SQL
6. Harnessed Excel
7. Utilized DAX Studio

Project video

Live Interactive Dashboard

SQL Project

AtilQ Hardware - Consumer Goods Analytics

Domain/Function: Executive Management

Consumer Goods Analytics"a deep-dive into performance insights for Atliq Hardwares, a leading name in computer hardware manufacturing. Atliq Hardwares was struggling to make data-driven strategic decisions due to a lack of clear insights. In a competitive and fast-paced market

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AtilQ Hardware - Consumer Goods Analytics

Consumer Goods Analytics" — a deep-dive into performance insights for Atliq Hardwares, a leading name in computer hardware manufacturing.

I took the lead on answering 10 ad-hoc business queries using SQL — transforming raw data into actionable insights for senior management

Project Details

Consumer Goods Analytics" — a deep-dive into performance insights for Atliq Hardwares, a leading name in computer hardware manufacturing.
🧩 Problem Statement:
Atliq Hardwares was struggling to make data-driven strategic decisions due to a lack of clear insights. In a competitive and fast-paced market, this posed a serious challenge.
💡 My Role:
I took the lead on answering 10 ad-hoc business queries using SQL — transforming raw data into actionable insights for senior management to make informed decisions.
🛠️ Tools & Tech Stack:
🔹 SQL – for writing powerful queries
🔹 MS Excel – to visualize and communicate insights
🔹 PowerPoint – to present findings with clarity
📈 Key Insights Delivered:
📌 Unique product count rose to 334 in 2021, up from 245 in 2020
💻 The Notebook segment had the most SKUs: 129 products
🧩 The Accessories segment added 34 new products in 2021
🛒 Flipkart led the discount race with 30.83% average pre-invoice discounts

Project video

Python Project

Telco Customer Churn Analysis

Domain/Function: Financial Domain

This project focuses on analyzing customer churn in a telecom company using the Telco Customer Churn dataset. Churn — when customers leave a service — is a major issue in competitive industries like telecom. The objective was to uncover patterns and factors that influence churn using Python.

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Visualizes churn distribution by gender and senior citizen status using count plots after importing and loading the dataset in Python using Pandas

Imports libraries, loads the Telco Customer Churn dataset, and displays key columns like gender, tenure, services, and churn for initial exploration.

Project Details

Telco Customer Churn Analysis
Overview
This project focuses on analyzing customer churn in a telecom company using the Telco Customer Churn dataset. Churn — when customers leave a service — is a major issue in competitive industries like telecom. The objective was to uncover patterns and factors that influence churn using Python and key libraries like Pandas, Matplotlib, and Seaborn.

The dataset contained data on 7,043 customers, including demographics, services subscribed, tenure, billing preferences, and contract details. The target variable, Churn, indicates whether a customer left the service (Yes/No).

Key Insights
🔸 Churn Rate: 26.5% (1 in 4 customers)
🔸 Senior Citizens had a churn rate of 42%, nearly double that of non-seniors (24%)
🔸 Customers without partners or dependents were more likely to churn
🔸 Fiber optic users churned at 41% vs 19% for DSL users
🔸 Lack of online security and tech support correlated with churn rates above 40%

Python Project

AtliQ Grands - Hospitality Analysis (EDA)

Domain/Function: Hospitality

To analyze booking, revenue, occupancy, and performance trends across Atliq’s hotel properties in various cities using datasets like fact_bookings, fact_aggregated_bookings, dim_rooms, dim_hotels, and dim_date. The aim is to generate actionable insights for improving operational efficiency.

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AtliQ Grands - Hospitality Analysis (EDA)

Initial exploration of hotel booking data including room types, guest count, booking status, and revenue for deeper hospitality analysis.

Bar chart visualizes booking platform usage frequency, highlighting 'Others' and 'Makeyourtrip' as top channels in the dataset.

Project Details

🏨 Atliq Hotel Booking & Revenue Analysis
This project analyzes booking, occupancy, and revenue trends across Atliq’s hotel properties using datasets such as fact_bookings, fact_aggregated_bookings, dim_rooms, dim_hotels, and dim_date. The goal is to uncover insights to improve operational efficiency and business outcomes in the hospitality sector.

🔍 Key Highlights
Presidential rooms had the highest occupancy (≈59.3%).
Delhi led city-wise occupancy (≈61.6%); weekend stays were significantly higher (72.39%) than weekdays (50.9%).
Mumbai generated the highest revenue (₹668M+).
Booking platforms like Makeyourtrip and Logtrip dominated.
Overbooking issues identified at certain properties.
Outlier cleaning done for guest counts and revenue.
Visualizations included: bar charts, descriptive stats, time-based analysis.

✅ Recommendations
Boost weekday occupancy via offers.
Resolve overbooking risks.
Promote direct booking strategies.
Focus investments in top-performing cities.

SQL Project

Healthcare Mangement

Domain/Function: Healthcare

Healthcare providers lack data-driven insights to optimize patient outcomes, reduce operational inefficiencies, and control healthcare costs. As a result, hospitals and doctors are unable to make strategic decisions regarding resource allocation, treatment efficacy, and financial planning.

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• Objective: Identify the most prevalent health issues in patients aged 60 and above.

• Objective: Determine which condition has the highest average billing.

Project Details

The healthcare industry faces several challenges that directly impact patient care, operational efficiency, and cost management. From your dataset, we can infer a realistic scenario:
To use patient, admission, treatment, and billing data to generate actionable insights that improve clinical outcomes, enhance hospital efficiency, and optimize financial performance.
Case Study 1: Common Conditions in Elderly Patients
Case Study 2: High-Billing Medical Conditions
Case Study 3: Top Performing Doctors
Case Study 4: Average Hospital Billing
Case Study 5: Emergency Care Leaders
Case Study 6: Insurance Billing Analysis
Case Study 7: Condition-Wise Healthcare Spending
Case Study 8: Diabetes Medication Trends
Case Study 9: Medication Patterns by Demographics
Case Study 10: Hospital Stay Duration Analysis

PowerBI Project

Blinkit Grocery Sales Analysis Dashboard (Power BI Project)

Domain/Function: Quick Commerce

This project presents an interactive Power BI dashboard analyzing sales, item performance, outlet efficiency, and regional trends for Blinkit – a fast-growing instant grocery delivery platform.

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Blinkit Grocery Sales Analysis Dashboard (Power BI Project)

Key Features 📈 KPI Cards: Total Sales, Average Sales, No. of Items, and Average Rating. 🛒 Sales Breakdown by Category: Insights into high-performing

🗺️ Outlet Location Analysis: Sales performance by Tier 1, Tier 2, and Tier 3 cities. 🧱 Outlet Size Performance: Comparison across small, medium

Project Details

Overview
This project presents an interactive Power BI dashboard analyzing sales, item performance, outlet efficiency, and regional trends for Blinkit – a fast-growing instant grocery delivery platform. The analysis is based on a structured dataset of grocery sales across different outlet types, sizes, and item categories.

The goal of this project is to uncover actionable insights to support strategic business decisions, such as product optimization, regional expansion, and marketing focus.
Objectives
Analyze total and average sales across outlet types and item categories.
Compare outlet performance by size, location tier, and establishment year.
Identify best-selling products and underperforming categories.
Evaluate customer satisfaction using average ratings.
Provide a dashboard for dynamic exploration via filters.

Hello, I am

Ashish Chauhan

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Excel-Sales and Finance Analytics Project of AtliQ Hardwares

AtliQ- Business Insights--360

AtliQ Grand--Hospitality Analytics

AtilQ Hardware - Consumer Goods Analytics

Telco Customer Churn Analysis

AtliQ Grands - Hospitality Analysis (EDA)

Healthcare Mangement

Blinkit Grocery Sales Analysis Dashboard (Power BI Project)

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Ashish Chauhan