Mandar Akkalwar

Loan Data Exploratory Analysis:

• Conducted exploratory data analysis (EDA) on a loan applications dataset (614 entries, 13 features including demographics, income, and credit history) to identify factors influencing loan approvals
• Utilized Python (pandas, NumPy) for data cleaning, transformation, and feature engineering (e.g., total income, log-transformed income)
• Imputed ~3.6% missing LoanAmount values using education-level means to maintain data integrity
• Created insightful visualizations using Matplotlib and Seaborn for univariate and bivariate analyses (distribution plots, box/violin plots, crosstabs)
• Discovered key trends: graduate applicants had higher average loan amounts; male applicants had more approved loans than female applicants
• Delivered actionable insights on loan approval patterns and demonstrated strong data-wrangling and visualization skills
• Completed data cleaning and data validation of existing spreadsheets to promote robust data management platform, resulting in accurate data analysis and entry.

1.Retail Sales Analytics Dashboard :

Tools Used: Power BI, DAX, Excel

• Designed and deployed an interactive retail sales dashboard in Power BI to provide real-time insights into business performance
• Consolidated and transformed raw sales and customer datasets to visualize Total Revenue, Customer Count, and Monthly Trends
• Integrated dynamic slicers for time-based filtering, enabling decision-makers to drill down into performance by month
• Empowered management with a clear view of financial health, boosting data-driven strategy and planning

2.HR Analytics Dashboard :

Tools Used: Power BI, DAX, Excel

• Created a data-rich HR analytics dashboard to track and visualize critical workforce KPIs such as Headcount, Attrition Rate, Average Age, and Average Salary
• Enabled breakdown by department, job role, and demographic segments, helping HR teams proactively identify high-risk employee groups
• Enhanced strategic workforce planning by delivering actionable insights through intuitive visualizations and data segmentation