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1. Introduction 2. Fundamentals of Information Engineering 2.1 Definition and Scope 2.2 Historical Development 2.3 Current Technologies 3. AI-Driven Data Pipelines 3.1 Understanding Data Pipelines 3.2 Role of AI in Data Pipelines 3.3 Comparative Analysis with Traditional Pipelines 4. Process Automation Essentials 4.1 Key Concepts in Automation 4.2 Benefits of Automation 4.3 Challenges and Limitations 5. Designing AI-Driven Pipelines 5.1 Requirements Gathering 5.2 Pipeline Architecture Design 5.3 Implementation Phases 5.4 Testing and Validation 6. Tools and Technologies 6.1 Popular AI Tools 6.2 Data Management Platforms 6.3 Automation Frameworks 7. Case Studies and Applications 7.1 Industry Use Cases 7.2 Successful Implementations 7.3 Lessons Learned 8. Future Trends and Research Directions 8.1 Emerging Technologies 8.2 Potential Innovations 8.3 Open Research Questions
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