35 lines
1.3 KiB
Markdown
Executable File
35 lines
1.3 KiB
Markdown
Executable File
# Executive Demo Guide
|
|
|
|
## Duration
|
|
|
|
30 to 45 minutes.
|
|
|
|
## Main Message
|
|
|
|
Oracle Deep Data Security protects data at the source. Even when an AI agent, vibe-coded application, BI tool, or dynamic SQL attempts to query more data than it should, the database enforces authorization by end user, role, and context.
|
|
|
|
## Demo Flow
|
|
|
|
1. Show the problem: an application or agent uses a powerful connection.
|
|
2. Run a risky request: "list all salaries and documents."
|
|
3. Show the excessive result in the baseline, when applicable.
|
|
4. Enable or explain the data grants.
|
|
5. Run the same query as a limited user.
|
|
6. Show that unauthorized rows and columns are filtered or masked.
|
|
7. Show a manager or HR user with broader authorized visibility.
|
|
8. Close with audit and governance evidence.
|
|
|
|
## Recommended Customer Track
|
|
|
|
1. `05-legacy-app-ai-extension`: safe legacy modernization with AI.
|
|
2. `06-rag-vector-classified-docs`: authorized chunk retrieval before LLM context injection.
|
|
3. `07-audit-evidence-data-safe`: evidence, auditing, and governance with Data Safe.
|
|
|
|
## Value Statements
|
|
|
|
- "Authorization follows the user, not only the application."
|
|
- "Controls live in the database, where the data resides."
|
|
- "Applications, agents, and BI tools respect the same data boundary."
|
|
- "The policy is declarative, versionable, and auditable."
|
|
|