Leveraged SQL and Excel to analyze Yellevate's client dispute data, identifying key factors contributing to payment refusals. Developed data-driven recommendations to mitigate disputes and improve revenue recovery.
Using data the company collected about these disputes, the following was performed:
Identified the problems facing the business and came up with objectives that can solve them with data analysis
Set data analysis goals according to these business objectives
Loaded a .csv file in SQL to perform the necessary data cleaning
Analyzed data using Excel
Visualized processed data
Generated insights from the analysis to provide recommendations on probable strategies to deal with disputes effectively
This Power BI dashboard analyzes social media performance across platforms by tracking impressions, engagement, clicks, CTR, and engagement rates. It highlights drop-off rates at each stage of the funnel, top-performing content categories, and optimal posting times by day and hour. Visual trends and comparisons help identify which platforms and content types drive the most impact.
a comprehensive health analysis dashboard that provides a 360-degree view of patient data, encompassing demographics, medical conditions, treatment costs, and provider information. This multi-page dashboard offers interactive visualizations to analyze patient distribution across various categories (age, gender, blood type, admission type), track trends in admissions over time, and gain insights into billing patterns and provider performance. By consolidating key metrics into a single, user-friendly interface, this dashboard empowers healthcare professionals to make informed decisions for improved patient outcomes and operational efficiency.
This comprehensive mobile phone sales analysis dashboard offers a detailed overview of sales performance, customer behavior, and product popularity across multiple dimensions. It highlights key metrics such as total revenue, units sold, customer count, and average selling price, all presented through visually engaging charts and maps. The dashboard encompasses various analytical perspectives, including overall sales performance, customer demographics, brand and model performance, and geographical distribution. Its visual-heavy design makes complex data easily digestible, enabling users to quickly identify trends, top-performing segments, and opportunities for strategic focus.
This interactive dashboard provides a high-level overview of real estate investment data across multiple cities and counties. It visualizes key metrics such as total property records, acreage by city and county, land type distribution, and geographic acquisition locations. Pie charts illustrate acreage and record distribution by state, while bar charts break down land use (agricultural, vacant, residential). Ideal for identifying high-opportunity areas and land use trends, this tool supports strategic investment decisions in the real estate sector.
This dashboard analyzes client behavior and revenue performance across different segments. It includes key metrics such as total revenue, lifetime value (LTV), number of transactions, retention period, and pause frequency. Visuals include bar charts for top-performing accounts, transaction volume, LTV rankings, and a time-series analysis of revenue from 2022 to 2024. Designed for strategic decision-making, this dashboard helps stakeholders identify high-value clients, behavioral trends, and long-term growth opportunities.
In this project, I explored the summer_medals dataset to analyze Olympic performance trends. Using SQL, I extracted and organized medal counts, separating Gold, Silver, and Bronze medals into different columns. I applied aggregation functions and window functions to calculate yearly totals and subtotals, making the data easier to interpret. This project highlights my skills in data extraction, transformation, and analysis using SQL for real-world datasets.
This project involved analyzing a comprehensive PostgreSQL database from GoodThought, a global NGO dedicated to education, healthcare, and sustainable development. I worked with datasets spanning from 2010 to 2023, including detailed records on assignments, donations, and donors.
Using SQL, I extracted and visualized insights to evaluate the effectiveness and reach of the NGO's projects. Key tasks included:
Identifying top-performing assignments by impact score and donation value.
Analyzing donor contributions by type and region.
Summarizing financial allocation to assess sustainability and funding distribution.
Key Skills Demonstrated:
Relational database querying (PostgreSQL)
Aggregation, joins, window functions, and conditional filtering in SQL
Data interpretation to inform strategic decision-making in the non-profit sector
Outcome:
The analysis highlighted which assignments made the greatest impact and which donor types contributed most significantly, providing actionable insights to guide future funding and operational strategies.