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In CRM Analytics, even if users are granted access to view an app and its dashboards, their ability to download data is controlled by permissions assigned via permission sets. Specifically, users need the "Download Data" permission to download data from widgets or dashboards. If this permission is missing from their permission set, they will be unable to download the specific widget, even though they can view the data.

In the Predictions page of a model within CRM Analytics (formerly Einstein Discovery), users have the capability to interact with the model to see how different input values affect predictions. Here's a detailed look at what can be accomplished:

Manual Input of Predictor Values: Users can manually input or change values for predictor fields to see how these changes alter the predicted outcomes. This is especially useful for testing hypothetical scenarios and understanding how sensitive the model is to various inputs.

Real-Time Interaction: This functionality provides a hands-on way to explore the model's behavior, offering immediate feedback on how input variations impact predictions, which can help in refining the model or in training users on its application.

Scenario Analysis: By adjusting predictor values, users can conduct scenario analyses, which are crucial for strategic planning and decision-making.

To improve the performance of local data sync in Universal Containers, evaluating the connection mode for each connected object is a practical approach. Here’s the rationale:

Optimization of Resources: Different connection modes (e.g., Full Sync, Incremental Sync) use different amounts of resources. Choosing the right mode for each object based on how frequently its data changes can optimize the sync process and reduce load times.

Efficient Data Handling: By tailoring the connection mode to the needs of specific data objects, the overall efficiency of the data sync process is improved, leading to faster refresh rates and more timely data availability.

Cost and Performance Balance: Evaluating and selecting the appropriate connection mode can also help balance performance needs with cost constraints, as some modes may consume more compute resources than others.

When uploading CSV files into CRM Analytics, column headers must follow certain formatting rules. Headers containing non-alphanumeric characters, such as "&**(&(%", will automatically be adjusted. Specifically, if the column header starts with non-alphanumeric characters or contains such characters, CRM Analytics will prefix the header with "X" to ensure compatibility with internal naming conventions. This behavior ensures that the column can be referenced in the platform without causing errors or conflicts.