A typical tuning session on a resource-constrained system starts with a search for "low-hanging fruit." In a CPU-bound database system, it would be the SQL that uses CPU the most, in an I/O-bound system, the SQL doing the most physical reads, and so on. Tuning the TOP statements often allows us to free large portions of the utilized resources and remove bottlenecks. Often, we can use AWR reports to quickly identify the SQL_IDs of the top statements in the database. But what if the AWR report reveals no "low-hanging fruit," and the resource usage is evenly distributed among multiple statements? Where do we start? Is there a better way to identify the starting point for the tuning of a resource-bound system? This presentation will explain when the AWR reports are misleading and how we can take a look at the data stored in AWR from a different angle to determine the top consumers. Discussion will include a practical demonstration using scripts for AWR mining that attendees can apply to their own challenging database performance tuning problems. Scripts and the demo log: https://github.com/MarisElsins/TOOLS/tree/master/SQL/C15LV_AWR