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Vaeshnavi Reddy Alla

Data Analyst • Dallas, TX • v************@gmail.com • 571****841 • drivetube.ai/•••••

Professional Summary

Data Analyst with 4+ years of experience delivering business intelligence, operational analytics, and reporting solutions across healthcare and enterprise environments. Experienced in analyzing 12M+ records, building executive Power BI and Tableau dashboards, automating reporting workflows with Azure data platform and Excel, and improving reporting accuracy through data validation and ETL support. Strong skills in SQL optimization, DAX, Python (Pandas), Azure Data Factory, and stakeholder collaboration to translate business requirements into scalable analytics solutions.

Technical Skills

Programming Languages: Python,R
Frameworks and Libraries: Pandas,NumPy,tidymodels
Databases: SQL,Azure SQL Database,SQL Server,MySQL,Snowflake
Cloud and DevOps: Azure Data Factory,Azure Data Lake Storage,Azure Synapse Analytics,Azure Blob Storage
Data and Analytics: Power BI,Tableau,DAX,Power Query,Power Pivot,ETL Pipelines,Data Transformation,Data Validation,Data Profiling,Reporting Automation,Excel,Operational Analytics,KPI Reporting,Root Cause Analysis,Forecasting
Tools and Methodologies: Git,GitHub,Azure DevOps,Jira,Agile
Excel & Productivity: PivotTables,XLOOKUP,INDEX,MATCH,Conditional Formatting
AI & Assistance: Microsoft Copilot,AI-assisted SQL development,Prompt Engineering

Work Experience

CVS Health
Data Analyst
04/2025 – Present
Worked at a national healthcare and retail pharmacy organization building operational analytics and executive reporting to support workforce productivity and SLA monitoring.
Tech Stack: Power BI, DAX, SQL, Azure SQL Database, Power Query, Power Pivot, Excel, Microsoft Copilot
  • Developed executive Power BI dashboards tracking 40+ operational KPIs across workforce productivity, backlog, turnaround time, and SLA compliance using star schema modeling and 50+ DAX measures, reducing executive reporting time by 45%.
  • Built enterprise SQL analytical workflows (CTEs, window functions, stored procedures) to analyze 12M+ operational records and identify workforce scheduling bottlenecks, enabling a 20% improvement in operational efficiency.
  • Automated weekly operational reporting by creating Azure SQL data marts and Excel Power Query/Power Pivot solutions that replaced 15+ manual reports and saved 18 analyst hours per month.
  • Designed a data quality validation framework using SQL reconciliation, duplicate detection, and exception reporting across 200+ attributes, improving reporting accuracy by 30% and reducing escalations.
  • Collaborated with operations managers and cross-functional stakeholders in Agile sprints to translate business requirements into analytics solutions, increasing stakeholder adoption and actionable usage of reports.
  • Accelerated SQL development and documentation using AI-assisted tools and query optimization techniques, improving ad-hoc analysis turnaround and maintaining consistent performance SLAs.
Cognizant Technology Solutions
Data Analyst
08/2022 – 06/2023
Provided analytics and reporting services within an IT services firm supporting enterprise clients' operational performance, SLA monitoring, and customer service analytics.
Tech Stack: Power BI, Tableau, SQL, Python, Power Query, Excel
  • Designed interactive Power BI and Tableau dashboards using star schema modeling, drill-through pages, and 35+ DAX measures to monitor SLA compliance and customer service KPIs for enterprise clients.
  • Developed optimized SQL reporting solutions using recursive CTEs, window functions, stored procedures, and PIVOT transformations to process 8M+ records, reducing report execution time by 35%.
  • Automated monthly operational reporting with Power Query, Power Pivot, and advanced Excel formulas, increasing analyst productivity by 40% and standardizing templates across teams.
  • Performed trend and root cause analysis by combining operational metrics and customer behavior data, identifying drivers of service issues and reducing reporting discrepancies by 25%.
  • Implemented data cleaning and transformation workflows in Python (Pandas, NumPy) to streamline ETL inputs and improve downstream report quality and consistency.
  • Coordinated with business and technical stakeholders to validate source systems, document business rules, and deliver executive reports used for client-facing strategic decisions.
Cognizant Technology Solutions
Junior Data Analyst
08/2020 – 07/2022
Supported reporting and ETL validation for enterprise clients at a global IT services company, focusing on data preparation, quality assurance, and recurring business reports.
Tech Stack: SQL, Power BI, Python, Azure Data Factory, Azure SQL Database, Excel
  • Authored SQL queries, joins, CTEs, and stored procedures to extract and prepare enterprise data for recurring reports and ad hoc analyses, improving report production efficiency by 30%.
  • Assisted in developing Power BI dashboards and Excel-based KPI reports that enabled business users to monitor operational performance and key metrics.
  • Performed data validation, reconciliation, duplicate detection, and referential integrity checks using SQL and Excel to ensure consistent data quality for reporting.
  • Supported ETL processes by validating source data, testing transformed datasets in Azure Data Factory, and documenting business rules for production deployments.
  • Automated repetitive reporting and data preparation tasks using SQL, Python (Pandas), and Excel macros, reducing manual effort and accelerating delivery timelines.
  • Collaborated with analysts, ETL developers, and stakeholders to troubleshoot reporting issues, gather requirements, and continuously improve reporting processes.

Projects

Retail Orders ETL & Sales Analytics
Tools Used: Python, Pandas, MySQL, SQL, Power BI, Git
  • Built an end-to-end ETL pipeline to ingest, clean, transform, and load retail order data into MySQL using Python and Pandas to enable downstream analytics.
  • Automated data cleansing, validation, and feature engineering to improve reporting accuracy and readiness for analysis.
  • Wrote optimized SQL queries to analyze sales performance, customer behavior, regional trends, and profitability.
  • Designed interactive Power BI dashboards visualizing revenue trends, customer segments, product performance, and executive KPIs.
  • Used Git/GitHub for version control and documented ETL workflows and database schema for maintainability.
Customer Churn Analytics for Credit Card Retention
Tools Used: R, tidymodels, SQL, Tableau
  • Analyzed 4,000+ customer records to identify behavior patterns and drivers of credit card churn.
  • Performed data cleaning, feature engineering, exploratory analysis, and predictive modeling using tidymodels in R.
  • Identified high-impact churn indicators and produced actionable insights to support targeted retention strategies.
  • Built interactive Tableau dashboards to monitor churn trends, segmentation, and key business KPIs for stakeholders.

Education

George Mason University
Master of Science, Data Analytics Engineering • 08/2023 – 05/2025
Anurag Group of Institutions
Bachelor of Technology, Electrical and Electronics Engineering • India • 07/2018 – 05/2022

Certifications

Google Data Analytics Professional Certificate — Google

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