the basic tasks in data management
Data management is generally a 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.
A competent market presence means, among other things, that the wishes and requirements of customers with regard to data provision are met quickly and reliably.
We classify the tasks in data management like this:
identify
- What kind of data objects are to be handled?
- What is the data source - where does it come from?
- Is there any given terminology "hidden" in the data?
- Can you see a defined data sovereignty for every single data object?
organize
- Where must the data be stored?
- What is the context to other data objects?
- How do you name the relationships between the data?
- Are they explicitly defined?
- Is data revision necessary?
- 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?
link
- How can I search for stored data?
- Which context / which metadata should be used for searching?
- How can several role-specific search strategies be established?
- How to avoid unnecessary copies of data?
publish
- Definition 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
- configuration of role and task-specific context views