Shri Vaasthsavi

Organized and dependable candidate successful at managing multiple priorities with a positive attitude. Willingness to take on added responsibilities to meet team goals. Detail-oriented team player with strong organizational skills. Ability to handle multiple projects simultaneously with a high degree of accuracy.

• Google Data Analytics Certificate
• Google Project Management Certification

Data Analytics Capstone Project
Google Data Analytics Certificate

Objective: Analyze customer purchase patterns and weather impact.
Tools Used: R, ggplot2, Tableau, R Markdown
Key Tasks:
Data cleaning and exploratory data analysis (EDA)
Predictive modeling to identify patterns
Interactive visualizations for findings
Outcome: Comprehensive case study demonstrating data analysis techniques and ensuring reproducibility and clarity through documentation.
Avocado Price Analysis

Objective: Investigate historical avocado prices and sales data across the United States.
Tools Used: R, Tableau
Key Tasks:
Data cleaning and transformation
Analysis of price trends and sales volume
Creation of dashboards and visualizations
Outcome: Actionable insights on market trends, aiding decision-making for stakeholders.

• Scholarship Recipient: Awarded for outstanding academic performance.
• Stock Market Predictive Analytics: Developed model with 90% accuracy using Python and R.
• Nonprofit Data Analysis Volunteer: Increased community engagement by 30% through strategic data analysis.

Case Study: Expanding the Vacation Rental Market

Objective: Analyze Airbnb data to determine the potential for a real estate management company to expand into a new vacation rental market.

Data Source: Publicly available Airbnb dataset from Kaggle.
Data Preparation: Cleaned and organized the dataset to ensure integrity, addressing missing values and standardizing formats.
Analysis: Aggregated data to identify trends and relationships between rental prices, occupancy rates, and neighborhood characteristics. Performed descriptive analysis using pivot tables and summary statistics.
Visualization: Created visualizations using ggplot2 in R and Tableau, including bar charts, scatter plots, and heat maps.
Findings: Identified neighborhoods with high rental prices and occupancy rates, particularly those with a higher density of super hosts and desirable amenities.
Recommendation: Suggested expansion into high-potential neighborhoods based on data insights.