Why Data Cleaning Matters More Than Extraction
TL;DR
Raw extraction gives you strings; data cleaning gives you intelligence. Learn why validation is the secret to scaling your SaaS or internal operations.
Raw extraction is just Step 1. If you extract "12/01/24" from an invoice, is it January 12th or December 1st? Without context and cleaning, that data is dangerous.
Data Validation: The Second Half of the Battle
Clean data is data that has been verified against business rules.
- Formats: Ensuring dates are in ISO-8601 (YYYY-MM-DD).
- Sanity Checks: Does the subtotal + tax equal the total?
- Normalization: Changing "Google Inc.", "GGL", and "Google" to a single unique Vendor ID.
How Extractify Solves This
Extractify focuses on this second step. While we use world-class models for extraction, our proprietary "Cleaning Engine" runs dozens of checks on every field to ensure it fits the expected schema of your target system.
FAQ: Common Questions on Data Cleaning
Is manual review still necessary? Yes, but only for "Low Confidence" results. Extractify reduces manual review by up to 90% by handling the obvious cases automatically.
Does this integrate with my existing ERP? Yes. Clean data is easy to export. We support CSV, JSON, and Excel formats that map directly to standard accounting software.
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