What does data preparation enable data engineers to do?

Data preparation is a critical step in the data pipeline that allows data engineers to process and refine data for further analysis or use in applications. It encompasses a variety of tasks that enhance data quality and ensure that the data is ready for its intended purpose.

One of the fundamental functions of data preparation is to map input attributes to XDM (Experience Data Model) attributes. This mapping ensures that the data adheres to a standardized format recognized across the Adobe Experience Platform, making it easier to integrate with other systems and applications.

In addition, data preparation allows data engineers to create calculated fields. Calculated fields can provide additional insights or metrics that are not present in the raw data, enhancing the value of the dataset. Mapping these newly created fields to XDM attributes further ensures they align with the platform's standards, facilitating better analysis and reporting.

Furthermore, transforming data types is another crucial aspect of data preparation. Data engineers may need to adjust data types to ensure compatibility among different data sources or to comply with the requirements of specific analytical tools. For example, converting a string field to a date format or changing an integer to a floating-point number can be vital for accurate data processing.

The option that encompasses all these individual tasks accurately reflects the comprehensive capabilities of data preparation within the