AI-supported improvement of data quality in NOGA code assignment
Improving data quality with AI: Automated classification of NOGA codes
A company from the sector Economic development and location development It manages a large amount of company data, including for statistical evaluations and economic analyses. A key problem: The automatic or manual assignment of NOGA codes was often inconsistent, error-prone, and opaque.This is especially true for new or unusual company names and job descriptions. To address this challenge, a new approach has been developed to improve data quality using AI.
Solution with Comitas: AI-supported classification based on GPT
Comitas developed a prototype together with the client, which used GPT-supported text analysis:
- Free text descriptions of companies analyzed
- Recognizes industry keywords and links them to official NOGA categories
- Provides suggestions with confidence values for selection
- Automatically flags inconsistent or missing entries.
The solution was embedded into the existing database environment and made usable via a simple web interface.
Result:
- Improving data consistency and significantly fewer manual corrections
- Transparent, documented suggestion logic for specialist departments
- Accelerated data maintenance and real-time quality monitoring
"The AI recognizes industry texts that are relevant for People difficult to categorize would be – and thus save us many manual assignments every day.” – Data controller (anonymous)
