The objectives of Business Data Quality focus on needs that provide operational advantages (eliminate redundancies, make the most of processes), prevent incidents or open new possibilities and lines of work.
It is necessary to clean data from different sources up to the ODS layer. The main goal is to obtain records that directly feed or form the basis of the Data Warehouse, and can eventually be exploited directly from other applications.
What final products will be obtained?
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Data loaded after cleaning and applying quality rules
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Linking data quality cases according to type and source
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Inventory of established business rules
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Definition of priority or weightings by source for matching / fuse
The medium-term goal is to obtain a complete Master Data Management system that allows full control over Data Management. Despite this, it is feasible to achieve the generation of reports and solvency metrics with an initial stage of Data Quality towards the ODS to ensure the availability of standardized data suitable for starting analyses.
The design and architecture of this solution must pay attention to the medium-term goal, establishing a proper methodology, good practices and ensuring a technological framework capable of supporting present and future needs.
It is necessary to determine confidence levels regarding the base information of the reports. In the Institutions, recibir datos de múltiples fuentes implica dificultades al momento de integrar esa información tanto en modelos de Data Warehouse, como en el establecimiento y creación de Datamarts y sistemas de Explotación.
Contar con información confiable y estandarizada le brindará a la Entidad la capacidad de tratar la información de manera unificada, con la seguridad de que no existen discrepancias con respecto a integridad, comprehensiveness, deduplication, etc.
