Part 2: Error Stack in SAP NetWeaver BI Provides Improved Data Load Error Handling

  • by Shreekant W. Shiralkar, Global Head, SAP Analytics CoE, Tata Consultancy
  • Amol Palekar, Principal Consultant, TekLink International, Inc.
  • Bharat Patel, SAP BW System Manager, Bharat Petroleum, India
  • June 1, 2008
See two scenarios that explain how to improve data load error handling by using an error stack and data transfer process. Learn about the impact of semantic key definition on data integrity and data inconsistency for a DataStore object.
Key Concept

In a data transfer process for a DataStore object (DSO) that has error handling enabled, the semantic key definition plays a critical role in maintaining the data consistency in the DSO. The semantic key determines whether the system should load the data record to the data target or send it to the error stack.

When your data warehouse acquires data from different source systems, the data is often riddled with data-related errors. You must cleanse and transform the data before loading it into the data targets on a regular basis. The error handling features in extraction, transformation, and loading (ETL) guarantee the quality of data. Although the options selected in your system determine how it processes and responds to errors, you must separate and correct the error records before loading them into the intended data target.

In this second article of a two-part series, we will discuss the different options available for error handling in SAP NetWeaver BI 7.0. Previously, we discussed the data transfer process (DTP) and error handling. We described how to leverage the error stack for a scenario with an InfoCube as the target. In this article we cover a variation for this process using DataStore objects (DSOs) as the target.

Using the error stack to maintain DSO data integrity requires special settings. Data fields are usually set by default to an overwrite mode. This means that if you load a record to the DSO that has an existing record with the same key field value, the system overwrites the data field value, replacing the previous value with the new value.

We will show you how to manage the data integrity between the On-Line Transactional Processing (OLTP) and the SAP NetWeaver BI system with the two examples of sales order data extracted from an OLTP system into a DSO in SAP NetWeaver BI.

In the first scenario, the master data for M34 was not loaded, so the system moved the data to the error stack. Upon correcting the error, you then must move this record out of the error stack and upload it the DSO.

The second scenario focuses on uploading a more complicated update. While loading new data for material M66 and updated data for M34, the system automatically shifts both sets of data to the error stack. The system sends M66 to the error stack because there is no master data maintained for it. It shifts M34 because the new information has the same semantic key definition as the old data for M34, which is present in the error stack and not yet loaded to the DSO.

Shreekant W. Shiralkar

Shreekant W. Shiralkar is a senior management professional with experience on leading and managing business functions as well as technology consulting. He has authored best selling books and published many white papers on technology. He also holds patents for innovations. Presently he is global head of the SAP Analytics Centre of Excellence at Tata Consultancy.

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Amol Palekar

Amol Palekar has worked on BI implementations for various Fortune 500 companies. He is currently principal consultant at TekLink International, Inc., and focuses on institutionalizing the global delivery model and processes for application development, maintenance, and support engagements. He is also a trainer, author, and regular speaker on the subject of BI. He is recognized for his popular and best-selling books: A Practical Guide to SAP NetWeaver BW (SAP PRESS) and Supply Chain Analytics with SAP BW (Tata McGraw-Hill).

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Bharat Patel

Bharat Patel is experienced in managing data warehouse technology for the petroleum industry. He is an SAP-certified BW and ABAP consultant, has authored a book on SAP BW, and teaches courses on BW and ABAP at the Sapient Academy and SAP Labs India. Bharat has presented papers about BW at Business Intelligence India Group (BIIG) conferences. He presently manages the SAP BW system at Bharat Petroleum, India.

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