What is the purpose of Aggregation in the ETL process?

The purpose of Aggregation in the ETL (Extract, Transform, Load) process is to summarize data and populate cube dimensions. This step involves taking detailed data and condensing it into a more manageable and insightful format. By summarizing data, Aggregation allows analysts and decision-makers to quickly understand trends and patterns within large datasets.

Aggregated data is often used in business intelligence and reporting, where it can help to accelerate analysis and improve the decision-making process. For example, in a data warehouse, Aggregation can create summary tables or cubes that provide quick access to important metrics without needing to query the entirety of the underlying detailed data.

Furthermore, Aggregation directly supports multidimensional analysis of data, enabling users to view information from different perspectives and dimensions, which is crucial for effective data analysis and business insights.