Sructured Database Environments
Across these projects, I demonstrated database management and SQL querying skills using MySQL in online IDE environments. I created and modified databases and tables, imported data from CSV files, and maintained data integrity with primary and foreign keys. I applied a variety of SQL queries and commands, including SELECT, COUNT, WHERE, GROUP BY, ORDER BY, INSERT, UPDATE, DELETE, and INNER JOIN, to organize, filter, and analyze data. I also generated output files from queries and adjusted table structures to meet evolving project requirements. These projects showcased my ability to structure raw data, extract insights, and provide actionable information for stakeholders efficiently.
This project involved performing a variety of SQL operations on multiple database tables to manage and analyze customer and order data. I imported datasets into MySQL tables, executed SELECT queries to filter and count records (e.g., customers in specific cities), and performed INSERT commands to add new customers and orders. I also ran UPDATE queries to modify fields such as order status and step, and used DELETE statements to remove records meeting specific criteria, demonstrating full CRUD (Create, Read, Update, Delete) operations.
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Additionally, I applied joins and filtering to analyze relationships between tables, counted records to validate query results, and exported query outputs to a CSV file for reporting purposes. This work highlights my proficiency in data management, query formulation, and database reporting, as well as my ability to maintain data accuracy while performing practical SQL tasks.
This project involved analyzing sales and return data using SQL queries to identify trends across regions and products. I wrote queries to determine the top-selling products nationally and within specific regions, as well as the most frequently returned items. By using SELECT, COUNT, INNER JOIN, and WHERE clauses, I filtered and aggregated data to highlight key patterns, such as Massachusetts having the highest sales and certain products being both top-selling and most returned.
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The analysis revealed actionable insights for the company, showing that the highest-selling product was also the most frequently returned. This suggests potential issues with product quality or fulfillment, emphasizing the importance of monitoring returns to maintain customer satisfaction and improve overall profitability. The work demonstrates skills in data querying, aggregation, and regional analysis to inform business decisions.
This project involved analyzing vehicle repair data to identify trends in part replacements and regional repair needs. Using a CSV file imported into a database, I applied SQL queries including SELECT, COUNT, WHERE, GROUP BY, and ORDER BY to organize the data and highlight patterns. The analysis revealed that the Midwest region had the highest number of repairs, the wheel arch was most frequently replaced due to rust or corrosion, and tires were the part most often repaired due to accidents or mechanical failures.
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The insights from this analysis allow the fleet maintenance team to make data-driven decisions about inventory distribution and maintenance scheduling. By structuring raw data into organized tables, I was able to quickly identify high-demand parts and regions, providing stakeholders with clear, actionable information to improve efficiency and reduce downtime across the fleet.
This project involved creating and managing a database using MySQL. I first created the QuantigrationUpdates database and then built three tables—Customers, Orders, and RMA—with the appropriate attributes, primary keys, and foreign keys based on an ERD. After setting up the tables, I imported CSV data into each table and used SQL queries to organize and analyze the data. Queries included SELECT, COUNT, WHERE, INSERT, UPDATE, DELETE, and INNER JOIN to retrieve specific information, such as orders from Framingham, Massachusetts, total customers in Massachusetts, updating order statuses, and deleting rejected RMA records.
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I also added new records to the Customers and Orders tables, and later renamed the Customers table to Collaborator to reflect updated requirements. Finally, I exported query results from the Orders table to a CSV file for reporting purposes. This project demonstrates skills in database creation, data import/export, data manipulation, and structured querying to provide actionable insights from raw data.