Which feature allows for combined datasets or transformations in CRM Analytics?

The chosen option, Data Recipes, is the correct answer as it allows users to create combined datasets and perform transformations on them effectively within CRM Analytics. Data Recipes are designed for tasks that involve data preparation, where you can define the rules for transforming and combining multiple datasets into a single, unified dataset that fits your analysis needs. This feature provides an intuitive interface to manipulate data, including filtering, aggregating, and joining datasets.

This makes Data Recipes particularly valuable for analytics projects, as users can streamline their data preparation processes without needing extensive knowledge of coding or complex data transformations. With the ability to visually manage and process data, Data Recipes empower users to easily refine data for specific analytical purposes, thus enhancing the overall efficiency of the analytic workflow.

Other options, while related to data management in CRM Analytics, serve different functions. Data Sync focuses on the ongoing synchronization of data between various sources rather than on transforming it. Dataset Builder is intended for creating datasets from scratch and may not have as robust capabilities for combining existing datasets with transformations as Data Recipes do. Dataflows facilitate data integration and loading but are generally used for ETL (Extract, Transform, Load) processes rather than interactive dataset manipulation.