Experienced data analyst with a strong background in SQL, Python, and data visualization tools. Skilled in extracting and analyzing real-time data from databases, applying advanced statistical techniques for forecasting and optimization, and creating interactive dashboards for tracking key performance indicators. Proven ability to provide actionable insights and support data-driven decision-making.
Data Analysis of AT&T Refurbished Data:
Utilized SQL for data extraction, manipulation, and summarization of AT&T refurbished test data.
Employed strategic SQL techniques such as indexing, query optimization, subqueries, and query tuning.
Gained a comprehensive understanding of Data Warehousing concepts such as Star Schema, Snowflake Schema, OLAP, and OLTP.
Analysis of COVID-19 Data:
Conducted in-depth analysis of COVID-19 data using Python libraries (Pandas, Matplotlib, and Seaborn).
Presented visualizations of data trends and insights using Tableau.
Received commendation for providing valuable insights and contributing to local pandemic response efforts.