aggregaattitietoja

Aggregeattitietoja is Finnish for aggregated data, referring to data that has been summarized from more granular observations. In aggregated data, each value represents a summary over a defined dimension such as time period, geographic area, or category, rather than a single, raw observation.

Aggregated data is produced by applying aggregation functions such as sum, count, average, minimum, and maximum to groups of records. In databases and data warehouses this is commonly achieved with operations like grouping by one or more dimensions, as well as rollups and cube calculations to create multi-level summaries. Aggregation reduces data volume and highlights overall patterns, trends, and comparisons, making it suited for reports, dashboards, and high-level analytics.

Common use cases include tracking totals and averages across time (for example, monthly sales totals), comparing categories (sales by product line), and presenting regional or demographic summaries (population by region). Aggregated data supports decision making by providing concise, scalable insights without exposing every individual observation.

Limitations and considerations accompany aggregation. Loss of granularity can obscure important variability and outliers, and ecological fallacy—drawing conclusions about individuals from group-level data—can lead to incorrect inferences. Aggregated data may still carry privacy risks if groups are small or can be linked with other information, so privacy protections and careful interpretation are important. Methods such as differential privacy are sometimes used to formalize these protections.

See also: data aggregation, data anonymization, statistics, business intelligence.