Contoso Usecase
This architecture prioritizes a real-time, event-driven data integration approach between SAP and Azure services, reducing dependency on file-based data exchanges.
| Component | Purpose & Benefits |
|---|---|
| OData API Sync | - Ensures real-time or scheduled data extraction from SAP. - Reduces dependency on batch jobs. |
| SAP CDC (Change Data Capture) Connector | - Captures only modified records instead of full data dumps. - Minimizes processing overhead on SAP systems. |
| Azure Data Factory (ADF) | - Orchestrates data movement and transformations. - Supports multiple source/destination types (e.g., MySQL, Oracle). - Can generate files (CSV, JSON, Parquet, Avro) if required. |
| Synapse Analytics | - Enables large-scale analytical workloads. - Enhances query performance for business reporting. |
| Power BI / Dashboarding | - Provides real-time analytics and visualization. - Supports multiple visualization tools for business insights. |
Even though this design moves away from traditional file-based integration, Azure Data Factory (ADF) still supports file generation when needed:
✅ File Formats → CSV, JSON, XML, Parquet, Avro
✅ Storage Options → Blob Storage, Data Lake, SFTP
✅ Triggers → Time-based, Event-driven, API-triggered
📌 Example:
- Instead of directly pushing data to Synapse, ADF can save data to Blob Storage in a structured format for later processing or external sharing.
- Files can be partitioned by date, region, or entity to enhance scalability.
| Advantages | Details |
|---|---|
| Faster Data Processing | Streaming eliminates waiting for batch files. |
| Less Storage Overhead | No need to maintain large files in storage. |
| More Secure | Reduces exposure to unauthorized file access. |
| Easier Data Governance | Ensures data integrity by avoiding version mismatches. |
| Scalable & Cloud-Native | Works efficiently across distributed cloud systems. |
| Reduces Manual Work | Eliminates file uploads, downloads, and manual processing. |
| Challenges | Possible Solutions |
|---|---|
| Some external systems still rely on files | ADF can generate files only when necessary. |
| Debugging may be harder | Implement logging & monitoring for API calls and CDC. |
| Potential API rate limits | Optimize API calls and use batching where possible. |
This cloud-native design leverages real-time API-driven data movement instead of batch-based file transfers. However, ADF still supports file generation when needed, ensuring flexibility.