Aufgaben im Datenmanagement

Data management is generally regarded as a "dry" and boring task and a "necessary evil". However, the key to simplified processes and the avoidance of unnecessary procedures ("muda") lies in the professional handling of data.


confident market presence also means, among other things, that the wishes and requirements of customers with regard to data provision and updating are met quickly and reliably.


We classify the tasks in data management in ...


  • What kind of data types are to be handled?
  • Is a clear terminology available for describing the data objects?
  • What is the data source - where does it come from?
  • Is there a clearly defined data sovereignity?


  • Where must the data be stored?
  • In what context does it stand in relation to other data?
  • How do you name the relationships between the data?
  • Are they clearly defined?
  • Is there a revision of the data?
  • Are role-based access rights defined?
  • How can the proliferation of Excel files be avoided?
  • How much additional data has to be entered when filing?


  • How can I search for stored data?
  • Which context / which metadata should be used for searching?
  • How can several role-specific search strategies be used?
  • How to avoid unnecessary copies of data?


  • Compilation of "views" of data from various sources
  • Mapping and export of various standard formats (eCl@ss, ETIM) at the push of a button
  • ad-hoc data sheets (pdf) in several languages
  • configure role and task-specific context views