Aggregatdaten

Aggregatdaten (German for "aggregate data") are data points that represent summarized information about a group rather than individual observations. They are produced by combining, counting, averaging or otherwise summarizing individual-level records into higher-level metrics such as totals, means, rates, proportions or distributional counts. Common aggregation units include geographic regions, time intervals, demographic groups or organizational units.

Aggregatdaten are used widely in statistics, public administration, business intelligence and research because they reduce data volume, support trend analysis and can protect individual privacy when shared. Examples include unemployment rates by district, average household income by year, and daily case counts in public health surveillance.

While aggregation reduces the visibility of individual records, it does not guarantee anonymity. Small subgroup sizes, detailed cross-tabulations or linkage with other datasets can permit re-identification. Accordingly, techniques such as minimum cell sizes, binning, top-coding and differential privacy are employed to manage disclosure risk. Aggregation also entails information loss and can introduce ecological fallacies when group-level relationships are ascribed to individuals.

Legal frameworks treat aggregated data differently from personal data: properly aggregated datasets that cannot be re-identified are generally outside the scope of personal-data regulations, but precaution is advised. Aggregatdaten remain a pragmatic tool to balance analytical utility and privacy protection, with appropriate methodological and governance safeguards.