Module 6: Data Flow & BW Objects (BW/4HANA 2.0)
This module explains how data actually moves through BW/4HANA, from source systems to reporting layers.
Understanding the data flow mechanics is essential for:
- Stable data loads
- Correct delta handling
- Performance optimization
- Troubleshooting production issues
1. Source Systems Overview
BW/4HANA can integrate data from SAP and non-SAP systems.
Common Source System Types
| Source Type | Examples |
|---|---|
| SAP ERP | ECC, S/4HANA |
| SAP BW | BW, BW/4HANA |
| SAP HANA | HANA tables, views |
| SAP SLT | Real-time replication |
| Non-SAP | Flat files, DB, APIs |
BW/4HANA favors ODP-based extraction over legacy methods.
Typical BW/4HANA Integration Scenarios
- S/4HANA → BW/4HANA (ODP)
- ECC → BW/4HANA (ODP)
- External DB → Open ODS View
- Real-time → SLT + Open ODS
2. DataSources (ODP-Based Extraction)
2.1 What is ODP?
ODP (Operational Data Provisioning) is SAP's strategic extraction framework.
It provides:
- Unified extraction
- Consistent delta handling
- Reduced complexity
2.2 ODP Contexts
| ODP Context | Usage |
|---|---|
| SAP (Extractors) | ECC / S/4 extractors |
| CDS | CDS-based extraction |
| BW | BW-to-BW extraction |
| SLT | Real-time replication |
| File | File-based extraction |
Always use ODP-based DataSources in BW/4HANA.
2.3 Why ODP Over Legacy Extraction?
| Aspect | Legacy | ODP |
|---|---|---|
| Delta | Fragile | Robust |
| Monitoring | Limited | Centralized |
| Performance | Lower | Optimized |
| Future | Deprecated | Strategic |
3. Transformations
3.1 What is a Transformation?
A Transformation defines how data is mapped and converted from:
- Source → Target (usually aDSO)
3.2 Types of Logic in Transformations
- Direct field mapping
- Formula-based mapping
- Routines
- AMDP-based logic
3.3 AMDP Transformations (Recommended)
AMDP transformations:
- Execute in HANA
- Enable pushdown
- Improve performance
Prefer AMDP routines over ABAP routines.
3.4 Where Transformations Fit in LSA++
- Technical mapping in acquisition
- Business logic in harmonization
- Minimal logic in reporting layers
4. DTP (Data Transfer Process)
4.1 What is a DTP?
A DTP controls:
- How data is moved
- When it is moved
- Whether it is full or delta
4.2 DTP Responsibilities
- Data selection
- Delta handling
- Error handling
- Load mode control
4.3 DTP Load Types
| Load Type | Description |
|---|---|
| Full | Complete reload |
| Delta | Incremental load |
| Repair | Error correction |
Delta logic is defined in the DataSource, executed by the DTP.
5. Request Lifecycle (Very Important)
5.1 What is a Request?
A request is a single data load execution.
5.2 Request Lifecycle Stages
Created
↓
Loaded
↓
Activated
↓
Available for Reporting
5.3 Request States
| Status | Meaning |
|---|---|
| Green | Successful |
| Yellow | Warning |
| Red | Error |
5.4 Request Management
- Requests can be deleted
- Requests can be reloaded
- Requests can be selectively repaired
Keep request sizes manageable for performance.
6. Error Handling Basics
6.1 Where Errors Can Occur
- Extraction (source)
- Transformation logic
- Data consistency checks
- Database constraints
6.2 Error Handling Options
- Error stack (PSA / inbound)
- Monitor in DTP
- Reprocess failed records
6.3 Common Error Types
| Error | Typical Cause |
|---|---|
| No delta | Wrong delta init |
| Short dump | Logic error |
| Duplicate records | Key mismatch |
| Conversion error | Data type issue |
Never fix data issues directly in targets — always correct upstream.
7. End-to-End Data Flow (Example)
Source System
↓
ODP DataSource
↓
Transformation
↓
DTP
↓
Staging aDSO
↓
Transformation
↓
Standard aDSO
↓
CompositeProvider
↓
BW Query
8. BW/4HANA vs Classic BW (Data Flow)
| Area | Classic BW | BW/4HANA |
|---|---|---|
| Extraction | Multiple frameworks | ODP |
| Pushdown | Limited | Strong |
| Transformations | ABAP-heavy | AMDP-preferred |
| Monitoring | Fragmented | Centralized |
9. Common Data Flow Mistakes
Mixing full and delta incorrectly
Ignoring request sizes
Using ABAP routines unnecessarily
Skipping error stack analysis
10. Interview-Grade Explanation
Q: Explain the BW/4HANA data flow.
Answer: In BW/4HANA, data is extracted using ODP-based DataSources, transformed using HANA-optimized transformations, transferred via DTPs, persisted in aDSOs, and consumed through CompositeProviders and BW Queries. Delta handling and error management are integral to the data flow.
11. Summary
- ODP is the strategic extraction framework
- Transformations map and enrich data
- DTP controls data movement
- Requests track load execution
- Proper error handling ensures data quality
12. What's Next?
➡️ Module 7: BW Queries – Basics
If your data flow is clean, most production issues disappear.