I help businesses and analysts transform raw data into accurate, reliable, and actionable datasets. This includes detecting errors, removing duplicates, standardizing formats, and validating data integrity for seamless analysis and reporting.
FAQs
I work with spreadsheets, databases, CSV files, JSON, and other structured datasets across industries like sales, finance, e-commerce, and more.
Yes, I can work in SQL Server, PostgreSQL, MySQL, Oracle, Snowflake, and other databases to clean, validate, and extract data efficiently.
Absolutely. I follow strict confidentiality protocols and never share client data without permission
Yes, I ensure datasets are ready for tools like Power BI, Google Data Studio, or machine learning models.
Yes, I can provide Python, SQL, or ETL scripts used during the cleaning/validation process so you can replicate or automate it in the future.
I use a structured QA workflow: first, data is loaded into a staging environment where cleaning rules are applied, validations and checks are performed, and only after approval is the clean, verified dataset delivered—ensuring accuracy and reliability.
I help businesses and analysts transform raw data into accurate, reliable, and actionable datasets. This includes detecting errors, removing duplicates, standardizing formats, and validating data integrity for seamless analysis and reporting.
FAQs
I work with spreadsheets, databases, CSV files, JSON, and other structured datasets across industries like sales, finance, e-commerce, and more.
Yes, I can work in SQL Server, PostgreSQL, MySQL, Oracle, Snowflake, and other databases to clean, validate, and extract data efficiently.
Absolutely. I follow strict confidentiality protocols and never share client data without permission
Yes, I ensure datasets are ready for tools like Power BI, Google Data Studio, or machine learning models.
Yes, I can provide Python, SQL, or ETL scripts used during the cleaning/validation process so you can replicate or automate it in the future.
I use a structured QA workflow: first, data is loaded into a staging environment where cleaning rules are applied, validations and checks are performed, and only after approval is the clean, verified dataset delivered—ensuring accuracy and reliability.