Monitoring and Data Quality Control of Financial Databases from a Process Control Perspective
نویسندگان
چکیده
The paper presents the application of several process control-related methods to the monitoring and control of data quality in financial databases. The quality control process itself can be seen as a classical control loop. Measurement of the data quality is conducted via application of quality tests, which exploit data redundancy defined by meta-information or extracted from data by statistical models. Appropriate processing and visualization of the test results enable human or automatic diagnosis of possible data quality problems. Selected model-based process monitoring methods are shown to be useful for detection, diagnosis, and, in some cases, also compensation of data quality problems. The test results are of interest not only for data quality control but also for business-relevant information extraction and monitoring. The presented methods are incorporated into our DQontrol product [1], and have been applied in the monitoring of a productive financial database at a customer site.
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