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Incomplete and inconsistent data, and the resulting derived information, leads to problems in the business processes,
delays the daily work and causes additional effort and thereby additional costs.
If strategic decisions are based on data that is insufficient or error-prone, then there is the danger,
that they will be wrong, with negative consequences for the company.
Bad data quality impairs compliance. Inadequate data quality, e.g. in clinical studies or in quality data,
is a risk factor for the company. Validated systems do not automatically guarantee good data quality.
These all are reasons to elevate and improve data quality.
Our offer
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We advise you on how to proceed in your specific situation,
determine the priorities together with you and stipulate a procedure model. |
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We measure the data quality of specific data sources according to your requirements
and make recommendations for the improvement of the data quality. |
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We implement comprehensive data quality concepts, train the personnel involved,
compile the necessary process descriptions and supervise the implementation. |
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We ascertain the data quality requirements for data warehouse applications and develop
proposals to improve the data quality in the data warehouse. |
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