Abhishek Aindla

Mount Pleasant,MI

Summary

Data-driven Business Analyst with over three years of experience in data analysis, visualization, and business intelligence. Adept at leveraging SQL, Tableau, Python, and Excel to extract meaningful insights and drive data-informed decision-making. Strong problem-solving and analytical skills with experience in automation, reporting, and KPI tracking. Passionate about optimizing processes and improving business operations through data-driven strategies.

Work History

Business Analyst | Systems Engineer

Savantis solutions

Developed automated reporting solutions using SQL, Excel, and VBA to optimize business insights.
Created interactive dashboards in Tableau to track key performance indicators (KPIs) and monitor business performance.
Designed and optimized SQL queries to retrieve, analyze, and visualize large datasets for improved decision-making.
Identified process inefficiencies and implemented data-driven improvements that enhanced operational efficiency.

Education

Master of Science - Information Systems

Central Michigan University

05.2025

Bachelor of Technology - Information Technology

Mahaveer Institute of Science and Technology

Skills

Data Analysis & BI Tools: SQL, Tableau, Power BI, Excel (VBA, Power Pivot, Macros)
Programming & Scripting: Python, R
Database Management: SQL Server, MySQL

Data Visualization: Tableau, Matplotlib, Seaborn
Process Automation & Optimization: VBA, Python scripting, Power Automate
Cloud & Big Data: Google Cloud (Data, ML, and AI tasks), AWS fundamentals

Websites

https://www.linkedin.com/feed/

Projects

Health Stream Management System|

Python, MySQL, Designed and developed a comprehensive healthcare system that integrates patient records, appointment scheduling, billing automation, staff management, and detailed analytical reporting.
Delivered dynamic, real-time dashboards using Matplotlib and Pandas; implemented a modular, scalable Tkinter interface to ensure intuitive navigation and seamless user experience.
Achieved successful deployment within a 7-week timeline, optimizing cost efficiency and system scalability.

Cryptocurrency Price Analysis|

Developed time-series models using LSTM to predict cryptocurrency price fluctuations.
Implemented a data pipeline with Python, SQL, and Pandas for data extraction, transformation, and loading (ETL).

Medical Cost Prediction using Regression|

Built a machine learning model to predict medical costs with Python (Scikit-learn).
Utilized SQL and Tableau to visualize and analyze cost trends across various demographics.

Timeline