Data Analyst Power Bi

SUMMARY

Abhigna Valambatla

+1-603-***-**** *****************@*****.*** LinkedIn

Data Analyst & Cloud Analytics Specialist with hands-on experience designing intelligent systems to automate, visualize, and scale data-driven decision-making across enterprise environments. Skilled in building predictive models, developing scalable ETL workflows, and deploying analytics solutions using Python, SQL, Power BI, and cloud platforms like Azure and AWS. Strong background in CI/CD integration, API development, and secure data orchestration. Adept at transforming raw data into actionable insights through dashboards, forecasting, and cross-functional collaboration. Projects span across mental health prediction (XGBoost + Shiny), Airbnb booking optimization, and enterprise security posture automation using Microsoft Graph API, GitLab, and Azure Active Directory.

EDUCATION

University of New Hampshire - Durham, NH

Peter T. Paul College of Business and Economics

Master of Science in Business Analytics September 2025 Course work: Probability and R, Business Intelligence, Linear and Logistic Regression, Statistical Methods, Optimization Methods, Python, Time Series, Big Data, Alteryx, Data Visualizations, Natural Learning Processing, Reinforcement Learning Jawaharlal Nehru Technological University – Hyderabad, India ACE Engineering College

Bachelor of Technology –Civil Engineering, July 2021 Course Work: Engineering Mathematics, Surveying & Remote Sensing, Construction Planning & Management, Estimation & Costing, Environmental Engineering, Geotechnical Engineering, CAD in Civil Engineering, Computer Programming, Python for Data Science, Operations Research

TECHNICAL SKILLS

Programming & Scripting:

Python (Pandas, NumPy, Matplotlib, XGBoost, CatBoost, TensorFlow, Keras, PyTorch), R, SQL, SAS, Web Scraping

(BeautifulSoup, Selenium), Flask, FastAPI, Machine Learning Algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forests, XGBoost, SVM, Naive Bayes, K-Means, LDA, Collaborative Filtering, ARIMA, Prophet), Natural Language Processing (NLP, Tokenization, SpaCy, TF-IDF), Computer Vision (OpenCV, CNNs), Statistical Analysis (A/B Testing, Hypothesis Testing, ANOVA, T-Test, Chi-Square)

Data Visualization & Analytics:

Power BI (DAX, RLS, Power BI Service), Tableau, Qlik, Excel (Pivot Tables, Power Query, Macros), Google Analytics, Alteryx, MS Office

Data Engineering & ETL:

Data Cleaning & Transformation, Data Modeling, Apache Airflow, SQL-based ETL, PySpark, Azure Data Lake, MySQL Cloud & Data Platforms:

AWS (S3, Lambda, Redshift, EC2), Microsoft Azure (Data Lake, Virtual Machine, App Service, DevOps), GCP (BigQuery), Snowflake, Databricks

Model Deployment & MLOps:

Docker, MLflow, GitHub Actions, Azure DevOps, Model Monitoring, CI/CD Pipelines, API Integration, Logging & Authentication Workflow & Version Control:

Git, GitHub, JIRA, Agile/Scrum Methodologies, VS Code, Postman WORK EXPERIENCE

Unitil Corporation – Portsmouth, NH

Energy Efficiency Business Intelligence Intern June 2025 – Present

• Migrated internal energy dashboards from Excel to Power BI, resulting in a 40% reduction in manual reporting time

• Developed and maintained interactive dashboards to track budget vs. actuals, QA/QC, and operational KPIs.

• Partnered with IT and stakeholders to streamline energy efficiency workflows, improving data availability and accuracy.

• Created training materials and delivered Power BI walkthroughs to staff, enhancing data literacy.

• Supported data integrity checks and automated nightly refresh cycles, improving efficiency of recurring reports. Tata Consultancy Services Pvt. Ltd.- Pune, India Feb 2022 – June 2024 Analyst

• Designed and implemented CI/CD pipelines using GitLab, ensuring smooth integration of data validation and transformation steps for analytics workflows.

• Pulled and centralized data from multiple tools into a unified dashboard to monitor the security posture across client departments, enabling real-time insights and data-driven decision-making.

• Automated user provisioning workflows using Azure Active Directory and Teams integration, reducing manual onboarding time and ensuring clean access control via scripting.

• Managed secret storage and data tokenization using HashiCorp Vault to ensure secure handling of sensitive information such as API keys and tokens.

• Developed and maintained databases (MySQL, Azure Data Lake) to support secure and efficient data access for analytics and reporting purposes.

• Utilized Microsoft Graph API and cloud tools (Azure, GCP) for data extraction and automation, contributing to streamlined reporting pipelines.

• Delivered Tableau dashboards and visualizations to communicate operational trends and team-level security metrics across departments.

• Conducted data quality audits and integrity checks on centralized logs and cloud-based data stores, enabling cleaner analytics reporting.

• Promoted cross-functional collaboration with development, security, and DevOps teams to align analytics goals with infrastructure planning.

• Organized company-wide training and awareness programs on Snyk, enhancing data security understanding and adoption across business units.

• Applied working knowledge of version control (Git) to manage and track analytics scripts, documentation, and pipeline configurations.

• Actively contributed to cloud data automation, applying knowledge of CyberArk, Fortanix, and other tools in compliance and data access monitoring.

• Resolved technical tickets related to database management, schema design, and user provisioning contributing to internal data governance processes.

ACADEMIC PROJECTS

• Airbnb Booking Performance Optimization (Python, XGBoost, CatBoost, Random Forest, Pandas) Built and evaluated predictive models using property features, location data, and seasonal demand to classify high-booking listings in Paris. Achieved 83.64% accuracy and 92.7% specificity with Random Forest. Identified key drivers like balconies, gardens, and Wi-Fi, and created actionable upgrade and pricing strategies to increase host revenue and occupancy.

• Burnout Risk Prediction App (R, XGBoost, Vetiver, Shiny, Docker) Built and deployed a regression-based XGBoost model to predict mental health risk using behavioral features (screen time, stress levels, caffeine, sleep, etc.). Served the model via a Vetiver-Plumber API and visualized outputs in a Shiny app. Converted continuous risk scores into binary “burnout” classification for user interpretability. Deployed the full stack using Docker and GitHub Actions to Hugging Face Spaces, with all components including .rds model, app.R, API script, and Dockerfile maintained in GitHub.

• TED Talk Performance Trends (Power BI, DAX, Data Visualization) Developed interactive Power BI dashboards to analyze TED Talk viewership metrics and sentiment trends. Used DAX measures and dynamic visuals to uncover patterns in audience engagement across topics, speaker ratings, and video length, enabling insight-driven recommendations for future content targeting.

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