What function does the Transform phase of ETL perform?

The Transform phase of ETL (Extract, Transform, Load) is crucial because it is during this phase that the raw data is processed to meet the needs of the analytical processes. This involves various operations such as data cleansing, aggregation, validation, and segmentation, allowing the data to be converted into a suitable format or structure for analysis.

In this phase, data might be aggregated to summarize key information or segmented to categorize data into distinct groups for more straightforward reporting and analysis. By performing these transformations, the data becomes more meaningful and useful for business intelligence tools and reporting.

Other options do not accurately describe the primary function of the Transform phase. For instance, loading data into user interfaces pertains more to the final stage of ETL or data presentation, while pulling data from the source layer relates specifically to the Extract phase. Creating initial data storage typically falls under the Load phase, during which transformed data is stored in a data warehouse or database for future access and querying. Thus, the Transform phase is pivotal in preparing and shaping data to ensure it is valuable and actionable for end-users.