I work in data cleaning, data merging, data formatting, and data splitting, helping transform raw, unstructured data into accurate, usable, and well-organized datasets. My role focuses on improving data quality and reliability so that teams can confidently analyze information and make informed decisions. I carefully identify and correct errors, handle missing or inconsistent values, remove duplicates, and ensure data follows consistent standards across all fields.

In data merging, I combine information from multiple sources while maintaining data integrity, resolving conflicts, and aligning structures to create a unified dataset. I also specialize in data formatting, ensuring that values such as dates, text, numbers, and categories follow the required formats for analysis, reporting, or system integration. This includes standardizing naming conventions and restructuring datasets to meet project or business requirements.

Data splitting is another key part of my work, where I divide datasets into meaningful segments based on specific criteria. This supports tasks such as analysis, modeling, validation, and reporting. I pay close attention to detail, accuracy, and consistency, understanding that even small data issues can significantly impact results.

Overall, I am committed to maintaining clean, structured, and dependable data. My work supports smoother workflows, better insights, and stronger outcomes across data-driven projects.