从 Oracle 传统数据库到 AI 就绪型数据库：零风险数据库现代化蓝图 [LRN3811].pdf

1、From Oracle Legacy to AI-Ready:A BlueprintDenis OSullivanSystems ConsultantQuest SoftwareFrom Oracle Legacy to AI-Ready:A BlueprintWhat this session is about and what it isntQuest Software|Confidential210/9/2025Database ModernizationHow to safely move data to cloud-native platformsHow to efficiently

2、 design cloud-native databasesAI ImplementationCreating RAGsVector DatabasesAI-Ready DataHow to get to a place where you are ready to use your Oracle data in AIGreatest impediments to AI success come from data management&identity securityQuest Software|Confidential310/9/202595%AI and ML projects enc

3、ounter data quality issues-MIT86%Companies experienced AI related security incidents in last year-Ciscos 2025 Cybersecurity Readiness Index 80%Companies faced increased security risks from unmanaged devices-Microsoft Digital Defense Report180ZB Growth of sensitive data and users in 2025(3x 2020 leve

4、ls)Where you are now can dictate where you go nextA benefit of legacy Oracle data is its structureQuest Software|Confidential410/9/2025Schema-on-writePre-defined schema structureFamiliar approachData is already structuredSchema-on-readSchema is defined when reading the dataMore flexibleSuitable for

5、unstructured data“The BlueprintTrusted data solutions for AI successQuest Software|Confidential610/9/2025Building trusted,high-quality data products through data modeling,intelligence,and governance Data Modeling Data Catalog Data Quality Semantic layer Data Governance Multiplatform Database Managem

6、ent Data movement to modern data platforms Database observability Data Trust Scores Bronze,Silver,Gold for Data Products Monitor data quality,data drift and bias to ensure accurate trustworthy data Autonomous agents using trusted data products in a workflow The GoalData ReadinessData Platform Readin