Power Bi Data Analyst

KAIVALYA PATKAR

Chicago, IL 414-***-**** **************.**@*****.***

QUALIFICATIONS PROFILE

Data-driven Business Analysis expert with 4+ years of experience optimizing SQL databases, streamlining ETL workflows using Azure Data Factory, and delivering insights via Power BI, Tableau and Office 365, driving cost-effective solutions and operational efficiency. EDUCATION

University of Wisconsin, Milwaukee

Master of Science, Data Analytics & MIS

PROFESSIONAL EXPERIENCE

Data Analyst at Illinois Department of Transportation, Springfield Oct 2024-Present

• Authored the Business Impact Analysis Document, verifying and revamping application relationships in MS Visio, increasing disaster recovery readiness by 15%.

• Lead the Power BI Dashboard project for the Hiring Department, enabling company-wide transparency & communication with CIO, CTO and Secretary of the Department of Transportation.

• Connected SharePoint list with Power BI, transferring the real-time requisition posting, increasing the dashboard efficiency by 20%.

• Employed Power Automate to eliminate the repetitive tasks, saving 5 hours per week along with seamless integration with the existing system.

Business Analyst Intern at Jagemann Stamping Company, Manitowoc Oct 2023-Dec 2023

• Spearheaded SQL optimization updates across 5+ related tables, ensuring 100% data consistency and integrity.

• Analyzed and mapped complex cardinalities & multiplicities in SQL database, accelerating database query performance by 30%.

• Configured Azure Data Factory to store Salesforce ERP data in ADLS Gen 2, assuring a centralized repository for further analysis.

• Employed Power BI reports & dashboards, reducing spending by 10% & reorganizing the resources towards new ventures.

• Proposed KPIs, Slicers & Decomposition Trees for insights about 70+ clients & 400+ SKUs, facilitating strategic decision-making.

• Built custom DAX measures and calculated columns to support time-intelligence calculations, uncovering inefficient clients.

• Refined ETL tasks using Power Query for data from MS Excel, CSV files, ERP & CRM, eliminating 95% of manual tasks. IT Analyst at University of Wisconsin, Milwaukee May 2023-Aug 2023

• Leveraged MS Excel formulas and Macros to automate an analysis of 25,000 records, enhancing data retrieval time by 25%.

• Enforced data governance standards by recommending data validation rules, reducing data entry errors by 20%.

• Improved the performance of datasets by indexing the schema in SQL, enhancing query execution & data retrieval time by 10%.

• Introduced report-level, page-level and drill-through filters in Power BI, revealing a 5% enrollment increase per semester.

• Optimized existing Power BI reports using Power Query Editor, reducing refresh time & allowing faster report generation. BI Developer at Bytes Arena, India Jan 2022-Jan 2023

• Introduced data-driven strategies, reducing expenses by $10,000 within the first quarter of employment.

• Utilized Excel pivot tables to summarize monthly benefits data, resulting in a 20% decrease in patient data discrepancies.

• Applied SQL and Python concepts to analyze large datasets from administration, increasing funding ratio optimization by 10%.

• Employed Power BI Reports to conduct cost analysis for client companies, improving budgeting accuracy by 12%.

• Extracted 10 gigabytes dataset using query folding & incremental refresh in Power BI, enhancing database performance.

• Performed comprehensive data audits, identifying and rectifying over 25 discrepancies, leading to a 98% accuracy rate. TECHNICAL SKILLS

Data Visualization Tools: Power BI, Tableau, Looker Programming Languages: SQL, Python, R Database Technologies: MS SQL, PostgreSQL Microsoft Tools: MS Excel, MS PowerPoint, MS Visio Version Control: GIT, GitHub Azure: Data Factory, Databricks, Data Lake, CosmosDB Project Management: Jira, Confluence Data Integration: Alteryx, Informatica PROJECTS

COVID-19 Power BI Analysis

• Analyzed global COVID-19 data in Tableau, identifying Key Indicators such as mortality rates, and vaccination coverage, daily susceptible, infected & recovered patients using 15 DAX and 20 Measures to deliver key insights. Financial Fraud Detection using Machine Learning & Deep Learning

• Conducted a machine learning analysis using Python Programming for detecting fraudulent transactions in a PCA-transformed, highly imbalanced dataset (492 frauds in 284,807 transactions).

• Transformed data using SMOTE to address imbalance and optimized models (Random Forest, Logistic Regression, ANN), achieving high precision and recall. Notably, Random Forest achieved an F1-score of 0.853 with near-perfect accuracy. Deployed the model on the web.

CERTIFICATIONS

• Microsoft Certified: Power BI Data Analyst (Power BI Certification Link)

• Microsoft Certified: Azure Data Engineer Associate (Azure Data Engineering Certification Link)

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