“Oracle Deep Data Security” was discussed recently at the Oracle AI World Singapore and it interested me to further study on how data security is evolving in the age of AI. The way data is accessed, processed and protected is changing dramatically with the rapid adoption of AI among the organizations. That’s why I thought it would be useful to explore Oracle Deep Data Security in a simple and practical way. In today’s world, data is everywhere. Businesses store customer data, financial transactions, employee records and much more inside databases. Earlier time, security was mostly handled at the application level. But this approach is no longer strong enough. With AI tools generating queries dynamically and multiple systems interacting with the same database, relying only on application level security creates risks. This is where Oracle introduces a new approach, moving security directly into the database itself. Oracle Deep Data Security is built on the idea that data shou...
“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 ...