Designing Enterprise AI-Ready Data Platforms

1. Introduction

• Why AI needs strong data foundations
• Enterprise complexity challenge

2. Key Components

• Data ingestion
• Storage (Lakehouse)
• Metadata & governance
• Data quality

3. Architecture Principles

• Scalability
• Security
• Reusability

4. Real-world considerations

• Legacy systems
• Integration challenges

5. Conclusion

• AI success = data architecture success