### 5.1 Performance Posture The dataset exhibits strong structural health with five dimension tables totaling 1,480 records, well within efficient query thresholds for analytical workloads. The largest table, **matches_1930_2022** (964 rows), accounts for 65% of total volume and contains free-text narrative fields that currently lack search optimization. With no foreign-key relationships detected across the five tables, query patterns likely involve independent table scans rather than complex joins, minimizing the risk of Cartesian explosion or index fragmentation. The primary scaling concern centers on text-heavy columns in the historical match archive, where unstructured commentary will degrade search performance as user queries grow in sophistication. ### 5.2 Key Optimizations | Target | Optimization Type | Recommendation | Strength | |--------|-------------------|----------------|----------| | matches_1930_2022.Notes | Text Search | tokenized_text | High | Implementing tokenized text search on the **Notes** column will enable rapid filtering and keyword discovery across 964 historical match records, directly supporting common use cases such as "find all penalty shootout matches" or "retrieve games with controversial officiating." This optimization transforms a linear scan operation into an indexed lookup, reducing query latency from seconds to milliseconds and unlocking natural-language exploration of World Cup narrative data. Given the dataset's modest footprint, this single enhancement addresses the most material performance gap without requiring broader infrastructure investment.