Information Quality Management

Use

Information Quality Management is an important factor for maintaining data. An exact data analysis is only possible if the quality of your data is good.

Data is integrated from heterogeneous sources in the data warehouse. You cannot assume that the data from the source system is already in a good state. There is frequently obsolete or incomplete data, or even redundancies. Possibly address data and other customer data was entered for other purposes and is therefore present in differing formats. In this case, inaccurate data can be corrected by cleaning up the data during the data analysis.

We provide you with various functions that will help you to detect and correct such inconsistencies in your data.

Features

Data Reconciliation

The data reconciliation for DataSources enables you to find data inconsistencies in the loaded data. The data loaded into the BW system is compared directly with the application data in the source system.

You can use the process for transaction data. This method can only be used with some restrictions for master data.

More information: Data Reconciliation

Handling Duplicate Data Records

DataSources for texts or attributes can transfer several data records with the same key into BW in one request. You can define how the BW system should handle these duplicate data records.

More information: Handling Duplicate Data Records

Detecting Incorrect Records when Updating Requests

Simulating data updates in an InfoProvider and debugging requests help you to analyze incorrect requests. With the simulation you can check if the corresponding transformation produces the expected results.

More information:

Data Flow with Transformation Simulating and Debugging DTP Requests
Data Flow with Transfer and Update Rules: Update Simulation in the Extraction Monitor

With error handling in the data transfer process / InfoPackage, you can control the behavior of the system when transferring data if incorrect data records occur.

More information:

Data Flow with Transformation Handling Data Records with Errors
Data Flow with Transfer and Update Rules: Handling Data Records with Errors

Master Data Consolidation with MDM

In earlier releases, you could use a solution that was integrated into the BW system. This function is now obsolete. Use the integration with SAP NetWeaver Process Integration as described in the MDM Configuration Guide instead.