Introduction

Scalable Data Pipelines with Oracle GoldenGate 23ai focuses on building real-time data integration systems. It enables high-speed data movement across multiple platforms. Oracle GoldenGate 23ai supports a microservices architecture. Therefore, it is well-suited for cloud-native and hybrid environments. It also ensures low-latency and reliable data replication across systems.

Learner Prerequisites

• Basic knowledge of databases and relational concepts
• Understanding of SQL queries and data handling
• Familiarity with Linux or Unix commands
• Awareness of ETL or data integration concepts
• Basic understanding of cloud platforms is helpful
• Exposure to distributed systems is an added advantage

Table of Contents

1. Introduction to Scalable Data Pipelines
1.1 Basics of data pipelines
1.2 Batch vs real-time processing
1.3 Challenges in scaling pipelines
1.4 Role of GoldenGate 23ai in modern systems

2. GoldenGate 23ai Architecture Overview
2.1 Classic and microservices architecture
2.2 Key components overview
2.3 Service-based architecture flow
2.4 Deployment models

3. Installation and Setup
3.1 System requirements
3.2 Installation steps
3.3 Configuration setup
3.4 Security configuration basics

4. Designing Scalable Pipelines
4.1 Pipeline design principles
4.2 Data flow planning
4.3 Parallel processing techniques
4.4 Performance considerations

5. Real-Time Data Processing
5.1 Change Data Capture (CDC)
5.2 Real-time streaming concepts
5.3 Integration with external systems
5.4 Use cases in analytics

6. Performance Optimization
6.1 Throughput improvement techniques
6.2 Latency reduction strategies
6.3 Resource utilization tuning
6.4 Monitoring performance metrics

7. High Availability & Recovery
7.1 Fault tolerance concepts
7.2 Recovery mechanisms
7.3 Backup strategies
7.4 Disaster recovery planning

8. Monitoring & Management
8.1 Monitoring tools overview
8.2 Logging and alerting
8.3 Performance dashboards
8.4 Troubleshooting methods

9. Security in Data Pipelines
9.1 Data encryption methods
9.2 Access control mechanisms
9.3 Secure communication setup
9.4 Compliance considerations

10. Cloud Deployment
10.1 Cloud architecture overview
10.2 Deployment on OCI/AWS/Azure
10.3 Container-based deployment
10.4 Cost optimization strategies

11. Advanced Data Processing
11.1 Data transformation techniques
11.2 Data enrichment strategies
11.3 Handling complex data formats
11.4 Integration with big data tools

12. Troubleshooting & Best Practices
12.1 Common issues and fixes
12.2 Debugging pipeline errors
12.3 Optimization best practices
12.4 Maintenance guidelines

13. Hands-on Implementation
13.1 Building a sample pipeline
13.2 Real-time streaming setup
13.3 Performance testing
13.4 End-to-end workflow

Conclusion

This training provides a complete understanding of scalable data pipeline design using Oracle GoldenGate 23ai. Moreover, it covers architecture, setup, real-time processing, and optimization techniques in detail. As a result, learners can confidently design efficient and scalable enterprise data systems. Finally, it prepares professionals to handle real-world data integration challenges in modern distributed environments.