SARAYU RAVI

Detail-oriented and analytical professional with over 5 years of experience in data-driven customer service, risk assessment, and operations. Skilled in collecting, organizing, and analyzing data to support business decisions and reporting. Proficient in SQL, Power BI, and Advanced Excel, with strong expertise in process documentation, issue resolution, and cross-functional collaboration. Adept at transforming raw data into actionable insights and communicating findings clearly. Actively transitioning into a full-time Data Analyst role, bringing a customer-focused mindset and a sharp analytical edge.

Preparing Data for Analysis using SQL – Coursera (2025)

Data Analytics Data Science – Kgisl Microcollege (Mar 2025 – Present)

• Healthcare Patient health Analysis using Ms-Excel
  Identified seasonal and regional trends impacting patient inflow, enabling proactive planning for high-demand periods (e.g., flu season).
• Provided actionable insights that informed hospital bed utilization strategies, staffing adjustments, and discharge planning improvements.
• Utilized Excel and Power Query to clean, transform, and prepare large healthcare datasets for analysis and visualization.
• Performed segmentation analysis to highlight high-risk patient groups with longer stays or frequent readmissions.
• Recommended improvements to discharge procedures based on time-series analysis, helping reduce average patient stay by identifying delays in discharge processing.
• Collaborated with stakeholders to present findings, ensuring clarity of insights for non-technical audiences through storytelling dashboards and visual summaries.
  Superstore Sales Analysis using Ms-Excel
• Conducted sales trend analysis across regions, segments, and categories using Excel pivot tables
• Identified key drivers of profit/loss and recommended discount strategy improvements
• Created interactive dashboards to visualize KPIs and support decision-making
• Presented insights that helped align sales strategy with profitability goals
  IMDB SQL Analysis – Movie Release Market Trends Using MySQL
  Designed and executed complex SQL queries to analyze IMDb movie data, extracting insights on genres, ratings, box office performance, and director/actor influence.
• Performed data cleaning and transformation on raw IMDb datasets using SQL JOINs, CASE statements, and WHERE clauses to ensure data accuracy and consistency.
• Identified top-rated movies by genre and year by leveraging SQL aggregate functions (AVG, COUNT, MAX, GROUP BY) and window functions (RANK)
• Analyzed the correlation between budget and revenue to uncover profitability trends across different genres and decades.
• Built SQL reports highlighting key metrics, such as most active directors, frequently collaborating actor pairs, and the evolution of average IMDb ratings over time.

Patient Admission & Discharge Analysis Using Tableau

• Collected and prepared hospital discharge data for visualization and analysis using Mackaroo.com
• Built interactive Tableau dashboards to track admission and discharge trends over time.
• Analyzed patient flow by department, diagnosis, and length of stay to identify capacity bottlenecks.
• Presented key performance indicators (KPIs) such as average length of stay, discharge rate, and readmission rate.
• Provided actionable insights to hospital administration to improve resource allocation and patient throughput.

• Analyzed global happiness scores using World Happiness Report datasets.
• Designed interactive Power BI dashboards to visualize scores by country, region, and year.
• Explored key factors such as GDP per capita, social support, life expectancy, and corruption perception.
• Identified regional patterns and trends in happiness levels across multiple years.
• Delivered insights on the strongest predictors of national happiness to support policy benchmarking.