DeeCeeSqueezer - Analysis and Improvement of Data Quality.


The DeeCeeSqueezer docks to your distributed documentation (Excel, Asset Management Systems, CMDB etc.) via standardized interfaces. The data is analyzed and reports show where improvements are needed.

The aim of using the Squeezer is to improve the data quality, to standardize it across disciplines and to prepare it optimally for a migration of the data into a new system.


Our "DeeCeeSqueezer" is the ideal solution whenever documentation and planning are currently taking place in several different systems and the data is to be migrated into a new, comprehensive system (CMDB, DCIM).

The quality of the data is checked and improved by DeeCeeSqueezer and thus optimally prepared for transfer to the new system.


Improvement of data quality takes place separately from the migration project
Consolidation and quality improvement takes place before the project of implementing new software. The separation of these two projects is an important success factor.

Requirements for the new target system are identified at an early stage
During the analysis of the existing data landscape, requirements for the new system are recognized, which are included in the selection or initial adjustment of this system.

Migration projects become easier to plan and more successful
Data consolidation and quality improvement is a project with several factors that cannot be planned exactly in time. By separating this process from the actual migration project, it becomes easier to plan and more successful.

Target systems are filled with higher quality data
Since the project pressure of the implementation process is largely eliminated, the data can be better prepared with more time and brought to a much higher level.

Increased efficiency in data correction
DeeCeeSqueezer ranks the errors with the highest impact on the overall result first. The time available for error corrections can therefore be used more efficiently.

Data migration takes place in a very short time
The time span between the replacement of the old documentation and the go-live of the new system is optimized. The target system is filled from one single data source. Errors due to different version statuses and errors in links were already transparent and corrected in advance.