### 1.2 Key Data Assets | Table | Role | Rows | % of Total | Size | |-------|------|-----:|----------:|-----:| | beer_ratings | dimension | 14,344,128 | 85.0% | 0.4 MB | | beers | dimension | 1,191,662 | 7.1% | 0.1 MB | | place_ratings | dimension | 385,707 | 2.3% | 0.0 MB | | beer_upcs | dimension | 249,348 | 1.5% | 0.0 MB | | users | dimension | 236,969 | 1.4% | 0.0 MB | The beer_ratings table dominates the dataset with 14.3 million rows—85% of all records—representing individual consumer evaluations of beer products. The beers catalog (1.2 million products) and users registry (237,000 reviewers) form the core reference entities, while place_ratings (386,000 venue reviews) and beer_upcs (249,000 barcode mappings) provide supplementary consumer feedback and product identification data. ### 1.1 Business Data Landscape This dataset represents a consumer beer rating and product catalog platform spanning 16.9 million records across 13 tables. The core entities include beer products (beers), consumer reviewers (users), breweries (brewers), retail locations, and geographic hierarchies (countries, states). The structure centers on two rating streams—beer_ratings capturing product evaluations and place_ratings documenting venue experiences—supported by product metadata (beer_upcs for retail barcodes, availability for distribution tracking) and geographic reference tables that organize brewers and availability by region. ### 1.3 Data Integration Posture Despite containing 13 tables, the dataset exhibits limited cross-table connectivity: zero of the 14 detected relationships are currently join-viable, indicating structural barriers to integrated analysis. While geographic tables (states, countries) and operational entities (brewers, availability, place_ratings, users) maintain validated foreign key relationships with 97% referential integrity, the dominant beer_ratings table—holding 85% of all data—appears isolated from the product catalog and user registry. This siloed posture constrains the ability to perform unified consumer analytics, such as linking individual ratings to brewer performance, tracking product sentiment across geographies, or analyzing reviewer behavior patterns across the 14.3 million evaluations captured in beer_ratings.