👋 Hello! I’m Bala Vikram Tadikonda, a Master’s student in Business Analytics at DePaul University, passionate about leveraging data to drive innovative solutions.

🌍 Based in: United States

🚀 Passionate about data analytics, business intelligence, and predictive modeling. I specialize in leveraging data-driven insights to optimize processes and drive strategic decision-making.

Business Data Analyst – Walgreens, USA
Oct 2024 – Present

• Delivered Power BI dashboards (DAX, Power Query) improving claims handling efficiency by 18%.
• Architected Azure data solutions (Data Factory, Synapse, Data Lake) integrating 20+ data sources.
• Migrated legacy systems to Azure SQL DW, reducing reporting latency by 35%.
• Implemented predictive analytics in Python, improving customer retention by 9.6%.
• Automated reporting (Python + Power Query), saving 40+ hours monthly.

Data Analyst – Bytes Tachnolab INC, India
Sep 2021 – Sep 2023

• Built ETL pipelines (Informatica, Talend), orchestrating 100+ jobs weekly and saving ₹5 Lakhs annually.
• Designed AWS Redshift data warehouse, improving scalability and reliability.
• Performed fraud detection & segmentation models, saving ₹10 Lakhs annually.
• Automated Python/SQL pipelines, accelerating reporting turnaround time.

Business Analyst – Bytes Tachnolab INC, India
Sep 2018 – Sep 2021

• Conducted stakeholder interviews, wrote BRDs/FRDs, and aligned analytics with business needs.
• Drove agile development with user stories and roadmaps.
• Led UAT with 95% user satisfaction post-release.
• Built Power BI dashboards, improving real-time decision-making by 25%.

🎓 Educational Journey:
🎓 Master’s in Business Analytics (Data Science) | DePaul University | GPA: 4.00/4.00 🌍 Based in: Chicago, USA
🖥️ Bachelor of Technology in Computer Science from SRK Institute of Technology—where my tech journey began.

💡 I Shine Brightest When:
Analyzing complex data sets and translating them into actionable strategies.
Crafting custom Power BI reports to enlighten decision making processes.
Collaborating with dynamic teams to design solutions that resonate with client needs.

🔨 Tech Toolkit:
Analytical Tools: Power BI, Financial Reporting, and Database Management
Soft Skills: Strategic Planning, Compliance Management, and Effective Communication

🌱 Currently Growing My Skills in: Advanced analytics techniques to predict trends and optimize business processes.

🤝 Let’s Collaborate On: Projects that challenge the status quo and require fresh, data driven perspectives to solve real world problems.

🎯 Professional Mission: To merge analytical rigor with creative problem solving, delivering solutions that not only meet but exceed business and community expectations.

📬 Reach Out! Let's connect and make something amazing together.
LinkedIn: Bala Vikram Tadikonda
Email: btadikon@depaul.edu

• Analyzed 24 years of retail theft data from Chicago to identify crime patterns, high-risk zones, store vulnerabilities, and arrest likelihood and built predictive models to forecast future incidents.
• Used Python (Pandas, Matplotlib, Scikit-learn, Prophet, TensorFlow), Geospatial tools (Folium, KMeans), and Tableau for end-to-end analysis. Applied ARIMA, Facebook Prophet, and LSTM for forecasting. Developed classification models like Random Forest, Logistic Regression, and XGBoost for predictive insights.
• Identified key theft trends, built an interactive Tableau dashboard, and proposed zero-cost, high-impact recommendations for retailers and law enforcement. This project enhanced my EDA, machine learning, and storytelling skills — and prepared me for real-world analyst roles.

• Processed and analyzed 337K+ safety event records to detect driver risk patterns.
• Developed machine learning models (Random Forest, XGBoost, Logistic Regression) achieving 90% accuracy.
• Conducted geospatial analysis (K-Means clustering, Folium heatmaps) to reduce accident-prone areas by 30%.
• Designed interactive dashboards in Tableau, Power BI for data visualization.

• Developed an integrated Tableau dashboard to analyze historical and current U.S. unemployment trends.
• Applied time-series forecasting models (ARIMA, seasonal decomposition) to predict unemployment rates through 2030.
• Created interactive maps, trend lines, and scatter plots for data-driven policy decision-making.