Rumina
Data Analyst
As a seasoned Data Analyst in London, I excel at leveraging data to drive business growth in the dynamic tech industry. With expertise in SQL, Python, and advanced data visualization tools, I transform complex data into actionable insights. I empower tech companies to harness data for innovation and success, focusing on optimizing operations, identifying trends, and uncovering opportunities. I am dedicated to helping organizations achieve their strategic goals through data analytics.
Hr Dashbaord
This HR dashboard tracks key workforce metrics, including total employees, salary comparisons by gender, education levels, job satisfaction, and attrition. It helps assess compensation trends and supports informed decisions in employee management.
Vacation Planing Project
In this project, our team of six collaborated to build a comprehensive PowerBI dashboard for vacation planning. We collected data from various websites and used Excel as our database. To prepare the data for visualization, we performed various cleaning and transforming techniques, including conditional formatting and VLOOKUP to search for duplicates and missing values. The cleaned data was then visualized using PowerBI, providing valuable insights for vacation planning
SQL Layoffs in Companies
In your SQL project, you explored company layoffs through various queries to uncover key trends and patterns. You examined the largest layoffs by company, location, industry, and year, identifying which sectors and regions were most affected. You also analyzed companies with 100% layoffs, mainly startups that went out of business, and explored how much funding these companies had raised. Advanced techniques like rolling totals and ranking by year provided insights into cumulative layoffs and top companies impacted over time. Overall, your project offered a comprehensive view of global layoff trends.
Python world population
I conducted data cleaning on the world population dataset using Pandas. This process involved identifying and addressing missing values, duplicates, and inconsistencies within the data. I standardized column names for better readability and ensured that the data types were appropriate for analysis. Additionally, I filtered out irrelevant entries to focus on the most pertinent information. This cleaning process enhanced the dataset's quality, making it ready for further analysis.
Customer Churn
This project analyzes customer churn using Power BI and Power Query to identify patterns, risk factors, and actionable insights for improving retention. The Customer Churn Dashboard provides a clear, visual overview of churn behavior across the customer base.
Key Insights:
Overall churn rate: ~14.5%, indicating that while most customers are retained, a notable portion is at risk.
Retention vs churn: Most customers are retained, but churn is concentrated among high-usage customers and those interacting frequently with customer support.
Customer tenure: Weak correlation with churn-both new and long-term customers may leave, highlighting the importance of continuous service quality.
Support calls: Customers who churn make significantly more support calls, making it a key early warning indicator.
Service usage: High-usage and complex-service customers (e.g., international calling) are at higher risk of churn.
Primary drivers: Service quality and customer experience are stronger predictors of churn than demographics or tenure.
Financial report
This project analyzes customer complaints across financial products to identify patterns that inform advisor workforce planning. By examining complaint volume and trends, the analysis helps determine where additional advisors are needed and where staffing levels can be optimized.
The project focuses on transforming customer feedback into data-driven insights that support operational and strategic decision-making. An interactive dashboard is used to visualize complaint trends and advisor demand across products.
This is an ongoing project, and additional analyses, refinements, and insights will be added as the work continues.