Data Quality Management

datamigration

The quality of the available data is a critical success factor for the acceptance and effectiveness of each (new) solution. Reaching the data quality level desired, is one of the largest challenges while implementing a system.

The static source data analysis as well as the process monitoring are thereby the first steps, which I would drive through for you. If on the basis of the results of the data integration into the data warehouse, a conclusion is implemented to the data sources, substantial improvements can be obtained.

My experience showed that data cleansing is just fixing the symptoms, but not the causes.

Sources of error can be permanently reduced by an integrated view on business processes and information systems. With my experiences within the range of large data sets, which are resulting from a multiplicity of business processes, I can support you actively within this range of error prevention.

The use of intelligent tools and methods is a possibility, in order to improve the data quality effectively. Thus concepts and best practices from the industrial surrounding field can be used, in order to implement a zero-error paradigm.

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Analyses & optimization of data quality

Approach

Technical execution