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The utilization of dataflows in Power BI is primarily focused on preparing data for reporting and analytics. Dataflows allow users to ingest, transform, and load data from various sources into the Power BI service. This preparation process enhances data quality, ensures consistency, and creates reusable data transformation processes that can be utilized in different reports and dashboards.

Using dataflows empowers organizations to centralize data preparation efforts, allowing multiple reports to draw from the same, clean, and transformed data. By leveraging the Power Query engine, dataflows provide flexibility in data transformation, allowing users to merge, filter, and reshape data as needed to better serve analytical needs.

In contrast, the other options suggest functions that do not align with the primary purpose of dataflows. For example, while one-time reporting might involve data preparation, it does not capture the ongoing nature and utility of dataflows in a dynamic reporting environment. Real-time data streaming is a different functionality, emphasizing immediate data consumption rather than preparation. Finally, while dashboards are a critical aspect of Power BI, they rely on prepared and modeled data, which is the domain of dataflows, rather than being limited to their design.