VENKATA PRAVALLIKA ADUSUMILLI

• Experienced Business Analyst with strong expertise in extracting, analyzing, and interpreting data using SQL, Excel, and Python.
• Experienced Business Analyst with a strong data analysis background, enhanced by the practical application of AI/ML for predictive insights, anomaly detection, and risk modeling. Skilled in using Python, R, and Azure ML tools to develop and deploy machine learning models in real business contexts.
• Proficient in data visualization and reporting using Tableau, with expertise in building predictive models and ETL pipelines.
• Adept at conducting stakeholder meetings, gathering business requirements, and creating process flow charts.
• Know how to work on Microsoft products (Word, PowerPoint, and Excel). Proficient in the Software Development Life Cycle (SDLC) phases, specializing in Planning, Analysis/Design, Development, Testing, and demonstrating strong teamwork and collaboration in cross-functional environments.
• Experienced in leveraging Azure DevOps for end-to-end project lifecycle management, including work item tracking, automated testing integration, ensuring alignment with Agile methodologies, and faster delivery cycles.
• Comfortable working independently or with a team, with limited supervision, and working under tighter schedules, meeting deadlines, and having the ability to learn on the fly.
• Excellent communication skills in facing the end users and training them in using the company product.
• Possess detailed and flexible attitudes, along with relationship building, team management, a friendly nature, a positive attitude, active listening, critical thinking, reliability and trustworthiness, a good work ethic, planning and organizing, strong work ethics, and time management skills. Strong knowledge of data governance frameworks, including data quality, metadata management, and lineage practices.

Business Analyst – Capstone Project

Project Title: Diabetes Health Prediction using Health Indicators

Tools: R studio and Python. 

• The study aims to develop a model to predict diabetes risk using health indicators and lifestyle factors, ultimately contributing to early detection and prevention.
• The research utilizes data from the 2023 CDC's BRFSS, focusing on key variables like BMI, blood pressure, smoking, and physical activity. Machine learning models, including Random Forest, Logistic Regression, and XGBoost, are employed to predict diabetes risk.
• Random Forest and XGBoost show strong performance in predicting diabetes risk, with BMI, high blood pressure, and age identified as significant predictors.
• The findings support the use of machine learning in healthcare for personalized risk assessment, early detection, and improved diabetes management, with potential benefits for individuals and healthcare systems.

Data Analyst – Data Visualisation Project

Project Title: Wealth by Sector: Unveiling the Dominant Industries of Billionaires
Tools: Tableau, Tableau Prep, Excel 

• Analyzed Forbes Billionaires data (2021–2023) to uncover sector-wise, regional, and demographic wealth trends among global billionaires.
• Cleaned and integrated over 6,000 data records using Tableau Prep, ensuring consistency across multi-year datasets.
• Created interactive dashboards in Tableau Desktop showcasing the distribution of billionaire wealth by industry, gender, geography, and age. Identified that Technology, Manufacturing, and Finance remained the most dominant wealth sectors consistently across three years. Revealed that the United States, China, and India housed the highest concentration of billionaires, with notable growth in India from 2021 to 2023., Visualized gender disparities, showing that male billionaires accounted for over 85%, yet the number of female billionaires increased steadily. Highlighted the age group of 50–70 as the most dominant among billionaires, providing insights into the lifecycle of wealth accumulation. Enabled data-driven insights for audience storytelling, delivering clear visual narratives around economic sectors and demographic trends.

• Achieved and sustained exceptional customer satisfaction ratings throughout projects and engagements.
• Demonstrated strong teamwork and collaboration skills through active participation in group projects and team-based initiatives.
• Good communication skills and innovative thinking.
• Time and stress management.
• Leader and pay attention to details.
• Adaptability to various environments.
• Critical thinker with strong problem-solving skills.
• Recognized for achieving high customer satisfaction ratings.
• Able to track requirements throughout SDLC lifecycle.