Map natural-language data concepts to profile schema fields with scoring.
npx skills add https://github.com/lytics/agent-skills --skill schema-discovery-lytics
Please help me install this Agent Skill. Skill: schema-discovery Source: https://github.com/lytics/agent-skills/tree/main/schema-discovery Command: npx skills add https://github.com/lytics/agent-skills --skill schema-discovery-lytics
Fetch and interpret the profile schema to identify relevant fields for data mapping and validation.
Find the profile field that matches a user description and return its name, type, and sample values.
High-intent search queries and answers about installing and using this skill.
You can map natural-language descriptions to profile schema fields by applying field inventory, candidate scoring, and value distributions to select the best matches for concepts like country, email, or signup date.
Schema discovery for data profiling is the process of fetching and interpreting the profile schema to list fields, types, and sample values for relevant data mapping and validation.
You identify field types and sample values by satisfying endpoints for listing fields, retrieving field info, and checking identity configuration to enable field selection and validation.
Yes, schema discovery validates data quality for segmentation by mapping described data concepts to actual profile schema fields and feeding the field info into audience-builder workflows.
The best way to select matching fields for common concepts like country and email is by applying candidate scoring and value distributions across the user table to map descriptions to concrete schema fields.
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