Pushkar Gadipalli
Professional Summary
Data Analyst with hands-on experience cleaning, validating, integrating, and analyzing operational and research datasets across healthcare, environmental policy, and business domains. Proficient in SQL for querying large record sets, Python and Pandas for ETL pipeline development, and Power BI and Tableau for building interactive dashboards and KPI-driven reporting. Experienced applying county-level FIPS data integration, CDC and EPA public datasets, and social vulnerability indices to surface actionable, policy-relevant findings. Developed recurring dashboards and structured research briefs that communicate complex quantitative trends to non-technical stakeholders. Holds an MSIS from Central Michigan University, an AWS Certified Cloud Practitioner credential, and a Lean Six Sigma Green Belt certification, reinforcing a strong foundation in data quality, process improvement, and cloud-aware analytics workflows.
Technical Skills
Work Experience
- Integrated EPA SDWIS/ECHO drinking-water quality data with CDC/ATSDR Social Vulnerability Index records across 83 Michigan counties using county-level FIPS codes to enable cross-dataset policy research.
- Engineered a Priority Score combining water-quality risk indicators and social vulnerability metrics, allowing stakeholders to rank counties by community need for targeted intervention.
- Built an interactive Power BI dashboard featuring KPI cards, county-level comparison visuals, and priority-tier indicators, translating complex environmental data into an accessible self-service reporting tool.
- Analyzed CDC Youth Risk Behavior Survey data in Excel using subgroup and trend analysis to identify disparities in poor mental-health outcomes across sex, grade level, and reporting periods.
- Authored policy-focused research briefs translating quantitative findings on water security and student mental health into structured recommendations for schools, government agencies, and youth-serving organizations.
- Conducted systematic quality reviews of datasets, calculations, and visualizations before final project submission, maintaining data integrity standards across all R&D deliverables.
- Queried and processed 1,000+ healthcare records weekly using SQL on an Impala platform, delivering structured datasets that fed directly into operational reporting for decision-makers.
- Designed and executed systematic data quality checks in SQL to catch inconsistencies in weekly healthcare record batches, improving the reliability of downstream reports used in operational planning.
- Cleaned and validated weekly record batches in Excel through filtering, deduplication, and formatting routines, transforming raw operational data into analysis-ready deliverables for stakeholders.
- Maintained detailed SQL query logs and validation documentation throughout the engagement, establishing a reproducible audit trail that supported knowledge transfer and minimized reporting errors.
- Progressed from supervised shadowing to fully independent query execution and reporting within six weeks, demonstrating the ability to own recurring analytical workflows with minimal oversight.
- Communicated data findings and quality issues through structured written documentation, ensuring stakeholders received clear, well-contextualized summaries of weekly operational data status.
Projects
- Analyzed drinking-water risk and social vulnerability across 83 Michigan counties by integrating EPA SDWIS/ECHO data with CDC/ATSDR Social Vulnerability Index records via county-level FIPS codes.
- Developed a composite Priority Score combining water-quality risk and social vulnerability indicators to identify communities requiring the greatest policy attention.
- Built an interactive Power BI dashboard with KPI tiles, county-level comparisons, and priority-tier breakdowns, enabling stakeholders to explore findings without analyst assistance.
- Translated quantitative dashboard findings into a policy research brief with actionable recommendations on water security and community resilience for Michigan county officials.
- Analyzed CDC Youth Risk Behavior Survey data to examine trends in poor mental health among U.S. high school students, segmenting results by sex, grade level, and reporting period.
- Performed subgroup and trend analysis in Excel to identify disparities in student mental-health indicators, producing charts and visual summaries that surfaced key longitudinal changes.
- Authored a policy-focused research brief translating quantitative findings into recommendations for schools and youth-serving organizations, connecting data trends to actionable program guidance.
- Analyzed 5,000+ customer transaction records using SQL to segment customer behavior and surface patterns relevant to business decision-making.
- Applied Python and Pandas to clean and transform raw transaction data, standardizing records for downstream visualization and reporting.
- Built an interactive Power BI dashboard with 4+ KPI visualizations, giving stakeholders a self-service reporting interface for customer segment performance.
- Documented analysis methods and metric definitions to ensure reproducibility and support clear communication of findings to non-technical decision-makers.
- Built a repeatable ETL pipeline using Python and Pandas to clean, validate, and transform 5,000+ sales records, improving data quality and ensuring reliable downstream reporting.
- Replaced a manual reporting process with an interactive Power BI dashboard tracking 4+ KPIs across sales performance, profitability, and regional trends.
- Surfaced actionable sales trends through visual analysis and structured documentation that directly informed inventory management and business planning decisions.
Education
Certifications
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