Let’s get into the nitty-gritty of how data validation and data mapping play into the world of data normalization. Ready to tame that data beast?
Data validation is how you make sure your data is correct and usable. It checks if:
Dates are actually dates
Numbers are within valid ranges
Emails are emails (not gibberish)
Think of it as spell-check for your spreadsheets. We plan on incoorporating the same within CSV Normalize, to make data normalization even easier!
What is mapping of data, you ask? Or what is a data map? It’s the process of matching fields from your source data (like your clean CSV file) to the corresponding fields in the destination system. Think of it like creating instructions: “This ‘Customer Name’ column in my CSV goes into the ‘ContactName’ field in the database.” You might use a visual tool or even a simple mapping file to define these connections. Effective database mapping relies heavily on having clean, predictable, normalized source data. Trying to create data maps from messy, inconsistent data is a recipe for frustration and errors.
Imagine you have a sample flat file containing customer orders exported from an old system. It might list the customer’s full address in every single row, have inconsistent product names, and maybe even some invalid email addresses.
Validation: First, you’d run data validation checks to fix those emails and flag questionable entries.
Normalization: Then, you’d apply the normalization data process. This might involve standardizing product names and perhaps (if moving to a real database) separating customer addresses into a different related table. Even in a CSV, you ensure consistency.
Mapping: Finally, with your clean data, you can easily perform data mapping to import those orders into your new sales system.
CSVNormalize can help:
Apply data maps to standardize field names
Run data validation on the fly
Output clean, normalized data ready for use
Clean data is happy data. When your files go from chaos to order, you:
Save time
Reduce errors
Make your systems more efficient
Whether you’re a developer, analyst, or just someone tired of fixing Excel errors, CSVNormalize is here to help.