Weiser’s YAML configuration streamlines data quality checks using a user-friendly syntax, ideal for version control and collaboration. The configuration file includes checks for orders existence with row count, revenue validation for completed orders with a minimum threshold, and customer data completeness, ensuring that no more than 5% of the email or phone fields are empty. The design is LLM-friendly, allowing AI to easily understand, generate, and modify the checks. AI can create Weiser configurations from natural language descriptions and self-document them through the inherently readable YAML structure. The framework also supports effortless updates and refinements by AI assistants, and provides smart suggestions for new checks based on the existing data schema, enhancing the overall efficiency and effectiveness of data quality management.
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