Which of the following functions helps shape data into a suitable form for Tableau?

The selection of Data Shaping as the correct answer highlights the importance of transforming and organizing data into a structure that can be effectively utilized by Tableau for analysis and visualization. Data shaping involves preparing your dataset by performing tasks such as pivoting, unpivoting, aggregating, and filtering, which are crucial steps to ensure the data is in the right format for Tableau to generate meaningful insights.

When you shape your data, you focus on restructuring it to fit the requirements of your analysis. This may involve adjusting the granularity, creating calculated fields, or merging data from different sources to produce a cohesive dataset. Such transformations enable Tableau to recognize dimensions and measures correctly, which facilitates building reports and dashboards more efficiently.

Other functions listed, such as Conditional Formatting, Field Formatting, and Report Designing, pertain to the presentation or visual aspects of data once it is already in Tableau. These functionalities enhance the appearance and usability of the data but do not fundamentally reshape the data itself for analysis. Therefore, choosing Data Shaping recognizes the essential preparatory work that lays the foundation for impactful data visualization in Tableau.