Data Analyst Supply Chain

PRASANTH YENUGANTI

Milwaukee, WI ***** ********.*****@*****.*** +1-414-***-**** [LinkedIn Profile] Professional Summary

Data Analyst with 3+ years of experience in predictive analytics, demand forecasting, and cloud-based data engineering. Proven track record supporting sales, supply chain, and nonprofit operations through data-driven planning. Skilled at developing scalable ETL pipelines, forecasting models, and interactive dashboards using Python, SQL, Power BI, and Azure. Adept at collaborating across Sales, Marketing, Operations, and Finance to improve demand planning accuracy and optimize resource allocation. Technical Skills

Programming & Scripting: Python (Pandas, NumPy, Scikit-learn), SQL, R, HTML/CSS Data Engineering & ETL: Azure Data Factory, Azure Synapse Analytics, Databricks, SAP Data Services, Azure Data Lake Gen2, CI/CD Pipelines

Analytics & Forecasting: Time Series Analysis, Predictive Modeling, Demand Forecasting, A/B Testing, Real-Time Data Processing Data Visualization & Reporting: Power BI, Tableau, MS SSRS, Excel (Dashboards, PivotTables) Cloud & Platforms: Microsoft Azure (Azure ML, ADF, Synapse), Git, SAP HANA IoT & Machine Learning: Sensor Integration, Predictive Maintenance, Real-Time Monitoring, Model Deployment Business Domains: Sales & Demand Planning, Supply Chain Analytics, Operations Optimization, Healthcare & Nonprofit Systems Soft Skills: Project Management, Cross-Functional Collaboration, Team Leadership, Oral Communication, Problem Solving Education

University of Wisconsin Milwaukee August 2022 – December 2023 MS in Information Technology Management (Specialization in AI & Data Analytics) GPA: 3.65/4.0

JNT University of Kakinada June 2017 – September 2021 BE in Electronics and Communication Engineering

GPA: 3.3/4.0

Professional Experience

Data Analyst August 2023 – Present

Red Cross, UW-Milwaukee, Milwaukee

Designed and implemented data collection and analysis systems using Python, SQL, and Power BI to track volunteer participation

Developed Power BI dashboards and SQL-based data pipelines to analyze volunteer engagement and event outcomes, reducing planning effort by 30% and improving visibility into campaign effectiveness.

Delivered actionable insights across regions through interactive reporting tools, helping leadership allocate resources more effectively across 20+ blood drives and community events.

Collaborated with Operations and Compliance to uphold safety and hygiene standards, achieving a 100% compliance rate during audits.

Trained and coordinated volunteer teams of up to 50 members, increasing team productivity by 25% and supporting smoother event logistics and strategic planning cycles.

Student Trainer - Sandburg Restaurant Operations September 2022 – December 2023 University of Wisconsin System

Managed food safety and quality control systems, ensuring compliance with FDA regulations and achieving a 15% improvement in inspection scores.

Supervised and trained a team of 15 student employees, implementing process improvements that increased productivity by 20%.

Utilized data analytics tools to monitor operational metrics, leading to a 30% increase in customer satisfaction ratings.

Recognized as "Employee of the Month" for exceptional leadership and contributions to team morale. Business Data Analyst August 2021 – July 2022

Tata Consultancy Services Hyderabad, India

Built and maintained 20+ scalable, parameterized data pipelines in Azure Data Factory, streamlining the movement of over 1TB of data monthly across staging and production environments.

Automated the daily ingestion of 500+ structured and semi-structured files into Azure Data Lake Gen2, significantly improving data availability and cutting manual effort by 40%.

Implemented incremental data load strategies from SQL Server sources, reducing pipeline runtime by 60% and improving data freshness for reporting dashboards.

Designed and managed core ADF components—including Linked Services, Datasets, Triggers, and control flow logic—to support reliable, end-to-end ETL workflows used by analytics and reporting teams. IoT & Data Analyst Intern May 2020 – June 2020

Pantech Solutions, India

Contributed to the development of a smart IoT solution that integrated 10+ sensor devices for real-time monitoring in a simulated industrial setup.

Applied machine learning algorithms (Random Forest, KNN) to detect anomalies and predict equipment failure with over 80% accuracy.

Built dashboards using Python and Power BI to visualize system performance, enabling early intervention and cost-saving decisions. Projects

Predictive Maintenance Analysis in Manufacturing

Objective: Minimize downtime and reduce costs through predictive analytics.

Extracted and processed data using APIs, Python libraries (Pandas, NumPy, Scikit-learn), and big data techniques.

Built interactive Tableau dashboards to visualize trends, enabling data-driven forecasting and strategic decision-making. Real-Time Data Processing with SAP HANA

Objective: Create a centralized data warehouse to enable analytics at scale.

Developed robust ETL workflows with SAP Data Services, ensuring seamless data transformation and integration.

Built high-performance data models in SAP HANA to support real-time analytics and enhance decision-making agility. IoT-Based Predictive Maintenance System

Built an IoT system to monitor equipment health and predict failures using machine learning algorithms.

Reduced maintenance costs by 20% and improved equipment lifespan through proactive interventions. Certifications & Training

Microsoft Azure Fundamentals certification (Microsoft)

Adult CPR/AED Certification (American Red Cross)

Power BI and Tableau Training (Coursera)

Microsoft Azure Data Engineer Certification

Completed 6 Months Microsoft Azure course

Key Achievements

Successfully implemented IoT and machine learning solutions to improve automation and predictive analytics in industrial environments.

Designed and deployed Power BI dashboards to enhance data visualization and decision-making for operational efficiency.

Recognized for leadership and process improvement initiatives, resulting in measurable increases in productivity and customer satisfaction.

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