### 1.1 Business Data Landscape This dataset, sourced from Kaggle, captures how AI tools are adopted and what effect they have on two audiences: students and working professionals. Everything lives in one table, **AI_Usage_and_Impact_on_Students_and_Professionals**, which holds 300 records, with each row most plausibly representing one respondent or user profile. Nettle classifies the table as a dimension, meaning it describes entities and their attributes rather than recording a stream of transactions. At 0.2 MB, it is a compact, self-contained reference sample suited to exploratory analysis rather than enterprise-scale reporting. ### 1.2 Key Data Assets | Table | Role | Rows | % of Total | Size | |-------|------|-----:|----------:|-----:| | AI_Usage_and_Impact_on_Students_and_Professionals | dimension | 300 | 100.0% | 0.2 MB | This single table is the entire dataset, so it accounts for 100% of rows by design rather than through concentration. It is a unified profile of AI usage and its observed impact, and it is the sole source for any insight drawn from this asset. With overall quality at 99% and completeness at 99%, it is a dependable foundation for descriptive analysis. ### 1.3 Data Integration Posture Nettle detected 0 inter-table relationships, and none are needed: a single table is self-contained, not fragmented or siloed. Referential integrity scores 100% because there are no cross-table links that could break. The practical next step is enrichment and schema evolution. Adding more respondents, or adding descriptive attributes over time, would broaden what leaders can learn without disturbing the current structure.