Improve Pivot Grid Intuitiveness

Feature Request: Improve Pivot Grid Intuitiveness

Summary:
Enhance the Pivot Grid user experience so that users can more easily discover, configure, and interpret pivoted data without needing prior training or deep familiarity with the interface. The feature should make common actions obvious, reduce confusion around drag-and-drop behavior, and provide clearer visual cues and guidance.

Problem Statement:
Currently, the Pivot Grid is not intuitive for many users. Key interactions such as adding/removing fields, changing row/column groupings, applying filters, and understanding where data is coming from are not clearly communicated in the interface. New or infrequent users often struggle to figure out how to build or adjust a pivot, leading to trial-and-error, frustration, and frequent help requests. This slows down analysis and reduces confidence in using the Pivot Grid for decision-making.

Proposed Solution:
Refine the Pivot Grid UI and interaction patterns to make core workflows more discoverable and self-explanatory:

• Add clearer visual affordances (icons, labels, and hover tooltips) for drag-and-drop areas (rows, columns, values, filters).

• Provide inline guidance or a brief “getting started” helper that highlights how to add fields, change groupings, and apply filters the first time a user opens the Pivot Grid.

• Improve field selection and organization (e.g., group related fields, show search, and distinguish measures vs. dimensions).

• Offer context-sensitive help or mini-explanations when users hover over key controls (e.g., aggregation options, sort controls).

• Ensure the layout adapts well to different screen sizes so that important controls remain visible and easy to access.

• Optionally provide a few pre-built pivot templates (e.g., by time period, by owner, by status) to demonstrate typical configurations and give users a quick starting point.

Benefits:

• Reduces the learning curve for new and occasional users of the Pivot Grid.

• Decreases time spent on trial-and-error configuration, speeding up analysis.

• Lowers support and training overhead by making the interface more self-explanatory.

• Increases adoption and effective use of the Pivot Grid for reporting and decision-making.

• Improves overall user satisfaction and perceived quality of the analytics experience.