### 5.1 Performance Posture The dataset consists of a single table, AI_Usage_and_Impact_on_Students_and_Professionals, with 300 rows. At this scale, storage layout and query speed are not a concern, and the current structure suits expected analysis such as filtering and summarizing by respondent group. The evidence does not show any column-level indexing, partitioning, or storage issues, so no speculative tuning is warranted. Scaling risk is low unless the survey grows by orders of magnitude. ### 5.2 Key Optimizations | Priority | Optimization | Status | |---|---|---| | High | None recommended at current data scale | No action required | With no high-priority items, there is no performance cost to recover, and analysts can expect near-instant responses on the existing 300 records. Because the table holds 100% of the data and no joins were validated, future effort is better spent on schema evolution, such as adding new survey waves or enrichment attributes, than on query tuning. Revisit performance only if row volume or concurrent users grow materially.