In many Databricks environments, large Delta tables are created without enabling standard optimization features like partitioning and Z-Ordering. Without these, queries scanning large datasets may read far more data than necessary, increasing execution time and compute usage. * **Partitioning** organizes data by a specified column to reduce scan scope. * **Z-Ordering** optimizes file sorting to minimize I/O during range queries or filters. * **Delta Format** enables additional optimizations like data skipping and compaction. Failing to use these features in high-volume tables often results in avoidable performance overhead and elevated spend, especially in environments with frequent exploratory queries or BI workloads.