Lakshmi Bhavani Cheekala

I’m a data analyst driven by curiosity and practical problem-solving. I combine SQL and Python with BI visualization to uncover patterns, validate data integrity, and translate insights into actions teams can execute quickly.

In my UPS Data Analyst Internship, I analyzed 200K+ load information records daily and built Power BI summary reports for senior stakeholders. I processed delivery data in MS SQL Server, wrote SQL queries to predict delivery error rates, and helped reduce delivery time by 11% while lowering shipping costs by 14%. I also ran data integrity checks and integrated a package barcoding workflow to improve warehouse productivity, contributing to a $1M revenue increase.

Through my MS in Computer Science (Data Science concentration), I strengthened my foundation in algorithms, DBMS, and statistical modeling. I apply that learning to projects like Disease Progression Analysis, where I used EDA and linear regression to find a 95% correlation between specific behaviors and advanced diabetes likelihood. I also worked on Weather Data Prediction, collaborating to clean historical datasets and build models for a 6-month forecast with 97% accuracy.

I enjoy building end-to-end solutions, too. With QuickFeed, I managed a team of eight in an Agile environment, helping design a roadmap and develop a web application’s core features—using Python for functionality and HTML, CSS, and JavaScript for the interface and user flows like login, search/navigation, and service rating—supported by test-case documentation for reliable iteration.