Data Quality Management

A major factor for the uptake and effectiveness of information systems in businesses is the quality of the underlying data. Frequently too little attention is paid to data quality management even though it plays a decisive role in the sustainability of the value added in data intensive business procedures.

The first step in data quality management is the definition of meaningful metrics that can accurately measure the current state of data quality in source systems. The next step is to analyze the relevant data-containing systems and to create a report based on the DQM metrics about the current state of data quality. Finally, software supported routines for data cleansing are developed and procedures for the sustained security of data quality are implemented. The DQM software tool Talend Open Profiler takes over the listed tasks and makes the development of a system for sustained data quality management possible.

We support our clients in the analysis of their data quality in their source systems and develop automated procedures for the sustained security of their data quality.