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Data Cleansing in Real Time Using BusinessObjects Data Services
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by Jeswin Davidson Ebenezer, SAP BusinessObjects Consultant, YASH Technologies
December 09, 2011
Extracting the right data from your transaction system for analysis and decision making is important. You can standardize and correct data using BusinessObjects Data Services. A real-time data migration example illustrates the concepts and walks you through the process. The scenario can help technical teams in any organization understand the data quality process for data migration. You can use this process in a non-SAP environment when data warehouses are built on top of relational database systems for reporting and analysis. You can also use it when the target is in an SAP system.
Key Concept
BusinessObjects Data Services is an information management application for data integration, data quality, data profiling, and text analysis. It allows users to integrate, transform, improve, and deliver trusted data that supports critical business processes so that they can make sound decisions on time.

Data cleansing is an important aspect of BusinessObjects because it allows companies to combine redundant records and streamline data for front-end users. BusinessObjects Data Services is an extraction, transformation, and loading (ETL) tool that combines two facets of data migration (i.e., data quality and data integration) in a single user interface.

SAP provides SAP Best Practices for Data Migration, which is a set of preconfigured data migration jobs using BusinessObjects Data Services to migrate legacy data to another system.  SAP Best Practices is available for two versions of BusinessObjects:

 

Note
This information is aimed at end users and developers who are interested in best practices regarding data cleansing.

This article is based on BusinessObjects Data Services 3.2. The process also holds good for BusinessObjects 4.0. Concepts are explained based on real-time data (i.e., transactional data used by any organization in its day-to-day activities), and how you get the data cleansed and ready to load.

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