Data Transformation with Excel, Python or SQL
Because messy data means messy decisions.
Your analysis is only as good as the data behind it. We clean, transform, and validate your spreadsheets or databases so they're accurate, consistent, and ready for use. From removing duplicates and fixing formatting errors to consolidating years of records across multiple sources, data cleanup ensures your reporting and analytics are built on solid ground.
Examples
- Clean 5 years of accounting spreadsheets for a mid-size business, fixing duplicates, correcting formulas, and standardizing formats.
- Normalize customer names and addresses across multiple spreadsheets so a retailer could get a single view of their clients.
- Migrate data from legacy systems into a modern SQL database, applying validation checks and fixing inconsistencies.
- Automate daily transformation of incoming sales data files to ensure reports always start from clean, consistent data.
- Geocode customer addresses to add latitude and longitude for mapping and spatial analysis.
FAQs
- Q: What does data transformation involve?
- A: It can include removing duplicates, fixing formatting errors, correcting inconsistent values, restructuring data tables, and validating entries against known standards.
- Q: Can you handle very large datasets?
- A: Yes. We use Python and SQL for handling large or complex datasets that Excel alone can't manage efficiently.
- Q: Do I need to know what's wrong with my data?
- A: Not necessarily. We can audit your data, identify issues, and recommend the right cleanup approach.
- Q: Can you automate the cleanup process?
- A: Yes. For recurring tasks like daily imports or monthly reconciliations, we can create automated scripts or workflows so your data is always ready to use.
- Q: What kind of businesses benefit from data cleanup?
- A: Any business that relies on reports, dashboards, or customer records. Clean data saves time, reduces mistakes, and improves decision-making.