One-sentence Explanation
This article introduces a hybrid data quality framework that replaces 1,000 brittle traditional business rules with only 3 AI calls, realizing automated and lightweight data quality verification.
Popular Understanding
We can use a daily physical examination as an analogy: originally, to conduct a comprehensive quality check on a batch of data, thousands of targeted verification rules needed to be written, such as data cannot be empty and the format must meet requirements, but these rules are easily invalidated with business adjustments. This hybrid framework completes the verification work through AI, requiring only 3 AI calls to cover a large number of complex original rules, and can flexibly adapt to business changes.
Application Scenarios
- Data quality verification of enterprise-level data warehouses
- Compliance check of order data on e-commerce platforms
- Transaction data quality audit of financial institutions
- Big data business scenarios that require frequent adjustment of verification rules
Related Concepts
The core concepts involved include: hybrid data quality framework, AI automated data verification, traditional business rule engine and so on.