Data quality checks - optimization of heterogeneous data landscapes

Incomplete and incorrect data, for example due to empty mandatory fields, incorrect links or inaccurate values, were a problem for subsequent analysis in many companies. The aim was a quantitative analysis of the company data in order to make it usable for marketing strategies and business optimization, for example.

In cooperation with CDQ AG, our Software & Information Engineering department took on the task of preparing heterogeneous data volumes for consistent use in a data analytics platform.

Procedure and cooperation

In order to create a homogeneous data structure, the data had to be checked using data quality checks before integration and incorrect data records had to be identified. In cooperation with CDQ AG, a leading institution for master data management, the implementation was carried out in two steps:

• CDQ AG was responsible for creating the data quality checks and for the design and methodology for revising the data.
• Our team implemented the data quality checks in the data analytics platform and ensured that they were optimally integrated into existing IT infrastructures.

This cooperation created an effective interface between industrial consulting and technical implementation, combining architectural and technical knowledge.

Results and benefits of the data quality checks

The implementation of the data quality checks led to:

• Increased data quality and improved consistency
• Optimized analyses through complete and cleansed data sets
• Efficient integration of heterogeneous data sources into a central platform
• Improved decision-making thanks to a high-quality database