Data quality

The beginning of a successful data management project

Start digitization correctly with high data quality

Measures which determine the foundations of your company’s data, should deliver what they promise. Therefore, an analysis of your data structures, as well as an analysis of the data sets themselves, is essential.

Performing a data analysis is useful at the beginning of a master data management project, in order to establish an initial overview of the data’s quality level. Therefore, the different data sources are analyzed.

Data analysis is a suitable measure for determining the status quo, as well as for providing information for planning further steps.


1. Data structure visualization

An inventory of the existing data models create an overview of the data structures. This will give you clarity about your database as well as the data records required for your master data project. Optimally, in the second step of data analysis, the quality of the data sets will be improved before the data is used for strategic decisions.

2. Data set analysis

On the basis of the specifications of the planned master data project, quality criteria are defined, which the data sets need to fulfill. In addition, duplicates are identified and eliminated.

Start your master data project with adjusted data sets, which keep their promise!


Further information about Data Rocket and Master Data