Designed and established efficient reporting mechanism by querying and extracting data from both MongoDB and MySQL databases

Streamlined data extraction, transformation, and loading processes, resulting in increased efficiency, reduced errors, and improved campaign performance

Developed a deep understanding of network performance analysis and demonstrated expertise in implementing an efficient and scalable system for monitoring and troubleshooting network issues

Developed data ETL pipeline using Python, Jupiter Notebook and T-SQL; rolled out usage across team of data analysts and product managers

Created a series of SQL queries to do funding source name cleaning, normalizing and transformation

Collected data using web crawling by Python and conducted data analysis of record linkage and name matching

Utilized Python and Pandas to extract insights from vast collections of online books and archives, providing users with streamlined and efficient access to valuable data resources

Successfully revamped data collection processes, leveraging best practices and advanced technologies to achieve a 35% reduction in processing time