dataforenkling
Dataforenkling is a term used to describe a structured approach to reducing the complexity of data ecosystems. It involves simplifying data models, reducing data volumes, standardizing formats and definitions, and improving data quality to make data easier to find, understand, and use.
The aims include enabling faster data processing, easier sharing between systems, reducing maintenance costs, and strengthening
Common methods encompass data minimization, schema simplification, standardization of field names and data types, deduplication, and
In public sector and enterprise contexts, dataforenkling can support easier citizen and customer interactions, streamline reporting,
Benefits include reduced processing time, lower storage and maintenance costs, smoother data integration, improved data quality
Challenges include risk of information loss through over-simplification, the need for ongoing governance, stakeholder alignment, and