Data requirements have to be changed quite often, e.g. because of new laws or business policies. This causes a change of the algorithms that identify poor data. In Business Intelligence tools, this change is cumbersome and costly and often requires a bureaucratic change process. A good Data Quality Management software contains a flexible and user-friendly rule management which facilitates the adjustment of data requirements within minutes.
2.Lack of Transparency
Business Intelligence systems often hide data requirements in program code. Thus, consumers of data quality reports cannot comprehend the exact assumptions made to identify poor data. Good Data Quality Management tools present the algorithms and their documentation together with data quality reports, so that consumers can follow the assumptions and easily identify potential errors in the assumptions. Moreover, this transparency generates trust in data quality reports and, therefore, leads to maximization of the added value of data quality reporting.
3.Lack of DQ-Functionalities
Relevant Data Quality features such as duplication checks, data profiling, or data enrichment are usually not part of Business Intelligence software. Such features are standard functionalities of leading Data Quality Management tools, since they are required to support an effective and efficient data quality management process.
4.Unnecessary Charge on BI Performance
Analyses for data quality management cause an extra work load for business intelligence systems. To avoid frustration of business intelligence users, a data quality management system should be separated from the business intelligence resources.
5.Complexity of Rule Management
The major origin for data requirements is the business. Only business experts know what good data / information has to look like, while IT departments usually focus on syntactical issues. Therefore, requirements should be managable by business staff without programming knowledge. In opposite to most Business Intelligence tools, most Data Quality Management tools contain such an easy-to-use rule management.
The Information Quality Institute has an excellent overview about the market for Data Quality Management tools. We can help you to pick the software that helps you best to control and improve your data quality.Don’t hesitate to contact us for a first consultation!