“Bring AI to Data” is a term I recently heard during the Oracle AI World in Singapore last week and it really caught my attention. It sounded simple but the idea behind it is quite powerful. So I thought it’s worth exploring a bit more! Normally, working with data and AI meant one thing, which is, moving data around. We would extract data from databases, send it to external tools or platforms, build machine learning models and then push the results back into the database. But this approach adds complexity, increases costs and introduces security risks. But now, Oracle is changing that model by bringing AI to where the data already is ! The concept of “Bring AI to Data” is straightforward but powerful. Instead of moving large volumes of data across systems, Oracle allows you to run AI and machine learning directly inside the database. This means that data do not have to leave its secure environment. This results faster processing, reduced data duplication, improved security ...
Performance tuning in Oracle Database often focuses on obvious areas like indexes, SQL rewrites etc. But some of the most impactful improvements can come from lesser known techniques. Here are 5 such tuning tricks that can make a real difference in production environments. Use SQL Plan Baselines to Stabilize Performance Even properly tuned queries in Oracle Database can suddenly degrade when execution plans change due to statistics refreshes or system upgrades. Using SQL Plan Baselines helps maintain stable and efficient execution plans, preventing unexpected performance regressions especially in highly changing workloads. SELECT * FROM DBA_SQL_PLAN_BASELINES; So, don’t just capture baselines, but periodically change them to allow the optimizer to adopt better plans when appropriate. Use Automatic Indexing Automatic Indexing is a useful feature in Oracle Database that can improve performance with minimal effort. It was introduced in Oracle Database 19c and enhance...