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Data quality

High quality data is critical for businesses and organizations. Incorrect data creates risks:

Automating becomes hard or impossible with bad data.

Incorrect data distorts the results of

Last but not least, bad data quality wastes the time and energy of (potentially highly paid) professionals.

For these reasons, improving data quality is essential to

An important means to test data quality is the detection of outliers.

Assessment of data quality

The assessment of data quality is usually a cyclic process to be carried out continuously or repetitively.

In order to assess the quality of data, it is necessary to define the target data quality. It might be one of

Data validation is an attempt to falsify the assumption that the claims of the data can be accepted as facts.

Data quality becomes increasinlgy important in unsuspected areas such as log files (event logs) because they can be analyzed for process mining.

Maintaining good data quality is often challanged by business agility requirements.