data-skill-hub

Use when you need to identify the real core dimensions of a table, compare competing base tables, analyze field distributions, evaluate mapping cardinality, explain gaps between image/video or source/result layers, or perform causal reasoning about why a dimension becomes '无', missing, skewed, or multi-mapped.

Use when you need to diagnose data quality problems in tables, SQL pipelines, bridge tables, path fields, enum fields, null-heavy dimensions, or frontend-vs-warehouse discrepancies. This skill traces issues to source pollution, SQL mapping mistakes, missing bridge keys, wrong grain selection, rule coverage gaps, or display-layer formatting.

资深Ray Data架构专家——以系统性思维分析数据下推与数据分发问题，输出生产可用的技术设计方案

用户行为深度分析专家——以数据驱动洞察，用RFM分层、留存分析、流失预测构建用户全景画像