Data Analyst Power Bi

HARSHITHA DEVI SUNKARA

Data Analyst

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Data Analyst with 3+ years of experience delivering actionable insights by building scalable dashboards, data pipelines, and statistical models. Proven ability to drive revenue growth and operational efficiency using Python, SQL, Tableau, and Azure. Skilled in collaborating across finance, operations, and engineering teams to implement data governance, automate reporting, and enhance decision-making. SKILLS

Programming: Python (Pandas, NumPy, SciPy, Matplotlib, Seaborn, TensorFlow, PySpark), SQL, R Databases: Microsoft SQL Server, PostgreSQL, MySQL Data Visualization: Tableau, Power BI, Excel (VLOOKUP, Pivot Tables) Statistical Analysis: A/B testing, Descriptive Statistics, Predictive Analytics, Hypothesis Testing, Time Series and Regression Analysis Cloud Platforms: Azure (Data Lake, Data Factory, Synapse), AWS (S3, EC2, Redshift), Snowflake ETL/Pipeline Tools: Alteryx, Talend, Apache Airflow, dbt Version Control: Git, GitHub

Methodologies: SDLC, Agile, Waterfall

Soft Skills: Analytical thinking, communication, detail-oriented, and stakeholder engagement EDUCATION

Master of Science in Information Systems, The University of Texas at Arlington December 2024 Bachelor of Technology, Andhra University, India April 2021 EXPERIENCE

Data Analyst BNY, Texas August 2024 - Present

• Performed comprehensive data mining and statistical analysis using Python (pandas, NumPy) and SQL to identify customer spending patterns, enabling targeted campaigns that generated $2.3M revenue growth.

• Conducted full lifecycle analysis gathering business requirements from stakeholders, designing complex Tableau dashboards using star schema and dimensional modeling that improved 25% executive decision-making efficiency.

• Developed advanced SQL queries with stored procedures and optimization techniques on OLAP databases, creating automated SSRS reports that reduced manual reporting time by 8 hours weekly.

• Collaborated with cross-functional engineering and finance teams to implement ETL workflows in Snowflake, establishing data governance standards that improved report accuracy.

• Designed performance monitoring dashboards tracking KPIs and SLAs using Tableau, implementing automated alerts and documentation standards that enhanced operational response times by 22% cost effectively. Data Analyst Sage Softtech, India August 2020 - December 2022

• Performed exploratory data analysis using Python (pandas, matplotlib, seaborn) and statistical techniques including correlation analysis and regression modeling to identify operational trends and patient flow patterns.

• Collaborated with product managers and stakeholders to gather requirements, extracting data from SQL/NoSQL databases and APIs to create unified datasets supporting 45 healthcare clinic operations.

• Implemented comprehensive data cleaning and preparation workflows, handling missing data and inconsistencies across 100K+ healthcare records while ensuring compliance and data governance standards.

• Built interactive Power BI dashboards and automated KPI tracking systems that monitor clinic performance metrics, enabling real-time operational decisions and reducing processing time.

• Established data pipeline documentation using Git version control, created reproducible analysis methods, and trained cross-functional teams on self-service analytics, reducing ad hoc requests by 35%. PROJECTS

Snowflake Data Warehouse & ETL Pipeline Using Medallion Architecture: Built a scalable 3-layer (Bronze, Silver, Gold) Data Warehouse using SQL with ETL pipelines for full/incremental extraction, staging, parsing, batch loading, and automated transformations using Snowflake Streams and Tasks. Applied SCD Type 1 and performed data cleaning, enrichment, type normalization, and outlier handling for data accuracy. Advanced Sales Analytics in SQL & Dashboarding with Tableau: Analyzed customer, product, and sales data in the Gold layer using SQL for dimensional exploration, ranking, segmentation, and time-series insights. Uncovered behavioral patterns and performance trends through part- to-whole, cumulative, and magnitude analysis. Visualized findings in an interactive Tableau dashboard with KPIs, product insights, top customer views, and year-over-year trends to support strategic, data-driven decision-making. Customer Segmentation Using KMeans Clustering - RFMAnalysis:Explored and cleaned data, retaining 406,309/541,911 transactions (77.3%) for meaningful customer analysis. Engineered Recency, Frequency, & Monetary (RFM) features to profile customers based on purchasing behavior. Applied K-Means clustering and determined the optimal number of clusters using Elbow and Silhouette methods. Identified 7 customer personas

(VIP, Churned, etc.) and visualized RFM scores to analyze spending and engagement. CERTIFICATIONS

Microsoft Certified: Azure Fundamentals (AZ-900) Graduate Certificate in Business Analytics SQL (Advanced) Certificate – HackerRank

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