Project Details

Objective:
The primary objective of this analysis is to examine customer transactions and credit profiles to identify a target group for the launch of the AtliQ Bank credit card. The study focuses on understanding spending behavior, risk assessment, and optimizing marketing strategies based on data-driven insights
Throughout this project, I have acquired expertise in the following areas:
1. Data Cleaning & Preprocessing
2. Handling missing values (mean/median imputation, occupation-based median income replacement)
3.Removing duplicate records
4.Outlier detection using Domain Knowledge (Banking), standard deviation & IQR method
5.Capping extreme values based on business constraints

Project Details

Project Details
In this project , I performed the following operations to get insights.
1. Data Cleaning- Handling missing values and outliers.
2. Data Transformation - Added occupancy% columns.
3. Insights generation-key questions answered
#calculating average occupaancy rate by room type and city.
# Identifying occupancy rate on weekdays and weekends.
# Analyzing revenue generated per city.
# Analyzing monthly revenue trends.
# Assessing revenue by booking platforms.

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.

1)Finance View: shows profit and loss statement like GM, NP, NS etc. and performance over time chart w.r.t to key metrices.
2)Sales View: Shows customers and product performance, unit economics and performance matrix by NS and GM%
3) Marketing View: Shows region and product performance, unit economics and performance matrix by NS and GM%
4)Supply Chain View: shows forecast accuracy, Net Error, trends and key metrices by customers and product.
5)Executive View: shows market share of competitors, trends, revenue by division and channel, top 5 customer

Live Interactive Dashboard

Project Details

1)Developed Power BI reports for Forggith Pharmaceuticals, enabling data-driven decision-making.

2)Created interactive dashboards to track sales revenue, distributor performance, and product trends, sliced by year, month, quarter, and team.

3)Analyzed $11.12bn in revenue, identifying top-performing distributors and assessing sales channels, locations, and product classes.

4)Conducted marketing performance analysis, evaluating revenue & volume achievement vs. targets.

5)Provided insights into sales representatives' and teams' performance across key market segments.

6)Leveraged DAX for advanced calculations and optimized dashboards for actionable intelligence.

7)Strengthened analytical skills in data visualization, KPI monitoring, and business performance analysis.

8)Key tools: Power BI, Excel, DAX.

Live Interactive Dashboard

Project Details

Key Topics Covered:
1)Problem Statements – Addressing 20 key business challenges in e-commerce data analytics.

2)Joins – Combining multiple tables (orders, products, sellers, customers) to generate meaningful insights.

3)Common Table Expressions (CTEs) – Simplifying complex queries for improved readability and efficiency.

4)Stored Procedures – Automating tasks such as identifying inactive sellers, analyzing product performance, and tracking order trends.

5)Functions – Creating reusable SQL functions for calculations and data transformations.

Project Details

In the "Consumer Goods Domain" project, I worked on database of Atliq Hardwares. Facing the challenge of data-informed decisions, I answered ten ad-hoc requests to extract actionable insights.
1)Findings revealed a substantial increase in unique products, a dominant 'Notebook' segment, and a flourishing 'Accessories' category.

2) Sales seasonality and the pivotal role of the 'Retailer' channel were uncovered.

3)Key learnings included the transformative potential of data analytics for informed decisions, the consumer goods market's dynamic nature, the value of product diversity, the significance of seasonality awareness, and the role of distribution channels in shaping sales outcomes.

4)The project enhanced my data analysis, problem-solving, and communication skills, contributing to my growth as a data analyst.