Dataschaal

Dataschaal is a Dutch term that translates to data scale and is used in several data-related discourses. Because Dutch technical language often relies on context, the exact meaning of dataschaal can vary between statistics, data visualization, and data processing. In statistics, dataschaal commonly refers to the measurement scale of data, known in Dutch as meetniveau, which includes nominal, ordinal, interval, and ratio scales. The chosen scale limits which mathematical operations and summaries are meaningful.

In data visualization and reporting, dataschaal can denote the axis scale of a chart or graph, such as lineair (linear) or logaritmisch (logarithmic), affecting how data patterns are perceived and interpreted.

In data processing and machine learning, dataschaal is frequently used to describe feature scaling or normalization, methods that adjust the range or distribution of data values—for example min–max scaling, standardization (z-score), or robust scaling—so that features contribute comparably to models.

In data architecture and governance, dataschaal may also refer to data granularity, from coarse summaries to fine-grained records, with implications for storage, privacy, and analytics performance.

Overall, dataschaal is a flexible umbrella term rather than a single, formal concept; its precise meaning is determined by the domain and the accompanying terms.