A data professional at the intersection of analytics and engineering, @datasavysarah_ with proficiency in Advanced SQL, Excel, Power BI, and Python for driven data-informed decision-making.
This project focuses on building and analyzing a Shop database using SQL to uncover actionable business insights.
The objective is to ensure reliable data through cleaning, then identify key sales trends and customer behavior patterns to support better decision-making.
This Power BI dashboard transforms raw pizza sales data into meaningful business intelligence and showcases my ability to build dashboards that balance analytics with visual clarity for decision-making.
The objective is to provide insights into sales trends, customer behavior, and operational performance through interactive visualizations.
Python Supermarket revenue analysis project providing comprehensive examination of sales transaction data, focusing on key business metrics and operational trends.
The analysis explores data cleaning process, revenue dynamics, product success metrics, payment method trends, and operational insights to facilitate data-driven business decisions in the restaurant industry.
SQL-based data cleaning and performance analysis project that transforms raw business data into reliable, analysis-ready datasets while extracting key performance metrics
This project standardizes a Mini Store data by their formats, validates data integrity, and creates clean datasets that serve as reliable sources for business intelligence.
Engineered a complete Emergency Room dataset from scratch using Python, then built an interactive Power BI dashboard to analyze 24 months of healthcare operations.
The objective was to build a scalable data generation framework using Python that produces realistic, structured healthcare data, then establish an efficient ETL process feeding into Power BI for real-time dashboard analytics and reporting.
This project demonstrates my expertise in SQL for business intelligence and supply chain management. Using advanced queries, I analyzed logistics, supplier performance, inventory risks, and cost optimization strategies to deliver actionable insights.
The project highlights my ability to transform raw data into meaningful KPIs that support operational excellence and strategic decision-making.
Python-based employee database system using MongoDB for data storage and Jupyter Notebook for complex querying. This project demonstrates advanced MongoDB operations, data generation, and query optimization techniques.