Data Transfer Process (DTP) and Error handling process:
Introduction about Data Transfer Process
1. You use the data transfer process (DTP) to transfer data within BI from a persistent object to another object in accordance with certain transformations and filters. In this respect, it replaces the data mart interface and the Info Package. As of SAP Net Weaver 2004s, the Info Package only loads data to the entry layer of BI (PSA).
2. The data transfer process makes the transfer processes in the data warehousing layer more transparent. Optimized parallel processing improves the performance of the transfer process .You can use the data transfer process to separate delta processes for different targets and you can use filter options between the persistent objects on various levels. For example, you can use filters between a Data Store object and an Info Cube.
3. Data transfer processes are used for standard data transfer, for real-time data acquisition and for accessing data directly.
Interesting Benefits of New Data Transfer Process
1. Loading data from one layer to others except Info sources.
2. Separation of delta mechanism for different data targets.
3. Enhanced filtering in dataflow.
4. Improved transparency of staging processes across data warehouse layers.
5. Improved performance : optimized parallelization
6. Enhanced error handling in the form of error stack
7. Enables real-time data acquisition.
Most important advantage in Data Transfer Process
1. Delta logic can be separately handled for separate data targets
2. Example for separation for delta logic
3. Delta logic is a part of DTP
4. One Source PSA
5. Two targets : One DSO keeping daily data and other one keeping weekly data
Five process for handling errors in DTP
Process#1 Enhanced Filtering, Debugging and error handling options
Process # 2 -Handling Data Records With Errors
1. Using the error handling settings on the Update tab page in the data transfer process, when data is transferred from a DTP source to a DTP target, you can specify how the system is to react if errors occur in the data records.
2. These settings were previously made in the Info Package. When using data transfer processes, Info Packages write to the PSA only. Error handling settings are therefore no longer made in the Info Package, but in the data transfer process
Process # 3 -Error Handling Features
1. Possibility to choose in the scheduler to
2. Abort process when errors occur
3. Process the correct records but do not allow reporting on them
4. Process the correct records and allow reporting on them
5. Number of wrong records which lead to a wrong request
6. Invalid records can be written into an error stack
7. Keys should be defined for error stack to enable the error handling of data store object
8. Temporary data storage can be switched on/off for each sub step of the loading process
9. Invalid records can be updated into data records after their correction
Process # 4 - Error Stack
1. Stores erroneous records
2. Keeps the right sequence of records à for consistent data store handling.
3. Key of error stack defines which data should be detained from the update after the erroneous data record.
4. After Correction, Error-DTP updates data from error stack to data target.
Note: Once the request in the source object is deleted, the related data records in error stack area automatically deleted.
1.
a. Key of Error Stack = Semantic Groups.
b. Subset of the key of the target object.
i. Max. 16 fields
ii. Defines which data should be detained from the update of erroneous data record (for data store object)
iii. The bigger the key, the fewer records will be written to the error stack
Process # 5 - Temporary Data Storage
2. In order to analyze the data at various stages you can activate the temporary storage in the DTP
3. This allows you to determine the reasons of error
Introduction about Data Transfer Process
1. You use the data transfer process (DTP) to transfer data within BI from a persistent object to another object in accordance with certain transformations and filters. In this respect, it replaces the data mart interface and the Info Package. As of SAP Net Weaver 2004s, the Info Package only loads data to the entry layer of BI (PSA).
2. The data transfer process makes the transfer processes in the data warehousing layer more transparent. Optimized parallel processing improves the performance of the transfer process .You can use the data transfer process to separate delta processes for different targets and you can use filter options between the persistent objects on various levels. For example, you can use filters between a Data Store object and an Info Cube.
3. Data transfer processes are used for standard data transfer, for real-time data acquisition and for accessing data directly.
Interesting Benefits of New Data Transfer Process
1. Loading data from one layer to others except Info sources.
2. Separation of delta mechanism for different data targets.
3. Enhanced filtering in dataflow.
4. Improved transparency of staging processes across data warehouse layers.
5. Improved performance : optimized parallelization
6. Enhanced error handling in the form of error stack
7. Enables real-time data acquisition.
Most important advantage in Data Transfer Process
1. Delta logic can be separately handled for separate data targets
2. Example for separation for delta logic
3. Delta logic is a part of DTP
4. One Source PSA
5. Two targets : One DSO keeping daily data and other one keeping weekly data
Five process for handling errors in DTP
Process#1 Enhanced Filtering, Debugging and error handling options
Process # 2 -Handling Data Records With Errors
1. Using the error handling settings on the Update tab page in the data transfer process, when data is transferred from a DTP source to a DTP target, you can specify how the system is to react if errors occur in the data records.
2. These settings were previously made in the Info Package. When using data transfer processes, Info Packages write to the PSA only. Error handling settings are therefore no longer made in the Info Package, but in the data transfer process
Process # 3 -Error Handling Features
1. Possibility to choose in the scheduler to
2. Abort process when errors occur
3. Process the correct records but do not allow reporting on them
4. Process the correct records and allow reporting on them
5. Number of wrong records which lead to a wrong request
6. Invalid records can be written into an error stack
7. Keys should be defined for error stack to enable the error handling of data store object
8. Temporary data storage can be switched on/off for each sub step of the loading process
9. Invalid records can be updated into data records after their correction
Process # 4 - Error Stack
1. Stores erroneous records
2. Keeps the right sequence of records à for consistent data store handling.
3. Key of error stack defines which data should be detained from the update after the erroneous data record.
4. After Correction, Error-DTP updates data from error stack to data target.
Note: Once the request in the source object is deleted, the related data records in error stack area automatically deleted.
1.
a. Key of Error Stack = Semantic Groups.
b. Subset of the key of the target object.
i. Max. 16 fields
ii. Defines which data should be detained from the update of erroneous data record (for data store object)
iii. The bigger the key, the fewer records will be written to the error stack
Process # 5 - Temporary Data Storage
2. In order to analyze the data at various stages you can activate the temporary storage in the DTP
3. This allows you to determine the reasons of error
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