Bharath Dharavath

Detail-oriented business analyst with a strong background in software development and data analysis. Proficient in Python, SQL, and JavaScript, leveraging these skills to accurately interpret business requirements, optimize workflows, and deliver data-driven solutions. Proven track record of collaborating with cross-functional teams to convert technical needs into actionable insights that align with business objectives. Recognized for exceptional problem-solving abilities, effective communication, and superior task prioritization skills, thriving in fast-paced and dynamic environments. Combining technical expertise with a focus on process improvement to consistently enhance efficiency and surpass stakeholder expectations.

• Python Programming
• SQL for Data Science
• Introduction to Tableau
• Digital Marketing Certification and Simternship
• Accenture - Data Analytics and Visualization Job Simulation
• Cognizant - Artificial Intelligence Job Simulation
• Quantium - Data Analytics Job Simulation
• British Airways - Data Science Job Simulation
• PwC Switzerland - Power BI Job Simulation

Brain Stroke Prediction: Gradient Boosting | KNIME
Utilized KNIME to create diverse machine learning models to predict the probability of a stroke. The most accurate model employed the Gradient Boosting approach and achieved an accuracy rate of 95%. Conducted exploratory data analysis (EDA) and provided business insights based on the key findings.

Prediction of Hotel Reservations: Python
Developed predictive models to estimate the likelihood of clients canceling their reservations. Utilized Lasso Regression and Cross Validation methodologies to provide accommodations with insights into the factors most influential in cancellations.

Hospital Management System: SQL
Created a Hospital Management System using MySQL as the DBMS to ensure efficient patient management, clinical documentation, inventory management, and laboratory information system. Utilized Visio to construct ERD diagrams to illustrate the relationships between tables.

Google Play Store: R Studio
Conducted exploratory data analysis (EDA) in R Studio and constructed visualizations to identify trends within the data. Developed a classification model to predict which factors influence the number of installations. Evaluated the performance of the model and provided recommendations to enhance future user satisfaction and drive business value.

Employee Attrition: Python
Developed machine learning algorithms to predict which factors lead employees to leave and identify parameters that affect employee attrition. Provided actionable recommendations to improve attrition rates and workplace satisfaction.