The most fundamental step is to ensure the underlying field in the Salesforce object has the correct data type (Currency or Number). If the field is a text or other non-numeric type, it cannot be summed in reports or dashboards, regardless of dashboard component settings. This is a common data model issue that an admin must address first.

A mix of lenses caters to different user needs and skill levels. Dashboard lenses provide curated, governed views. Story lenses allow for narrative exploration of insights. Dataset lenses empower proficient users to create their own charts. This balanced approach supports both guided consumption and self-service, which is a key goal for an Analytics home page.

Dynamic dashboards with relative date filters (like ‘Last Fiscal Quarter’) are evaluated in the context of the viewing user. This includes their personal fiscal year settings, time zone, and locale. If the EMEA rep’s company fiscal year is defined differently, ‘Last Fiscal Quarter’ will calculate based on their settings, potentially showing a different date range and thus different data than an admin testing in the system context.

The security best practice is to follow the principle of least privilege: start with no access. Then, use groups (public groups, role hierarchies, permission set groups) and permission sets to grant access systematically based on job function or team. This is more scalable and manageable than assigning permissions directly to users or using overly broad folder permissions.

The core logic for data transformation should reside as close to the source as possible. Adding the calculation to the underlying report ensures consistency (any dashboard or user viewing that report sees the same logic), reusability (other dashboards can use the same report), and maintainability (formulas are managed in one place: the report). Dashboard-level calculations are limited and can create fragmentation.

Dashboard interactivity (like clicking a chart to filter others) relies on the source report’s cross-filter capabilities. If the cross-filter isn’t functioning correctly in the standalone report, it will not work in the dashboard. The first troubleshooting step is to isolate the issue by testing the report’s cross-filter behavior independently, before considering dashboard-level settings or user context.

This is a key architectural concept. A dashboard filter is a centralized control that can simultaneously filter multiple components (charts, tables, etc.), even if those components are based on different source reports. A filter within a report only filters the data for that specific report. Dashboard filters provide a unified user experience for slicing dashboard data.

Performance best practices include designing focused dashboards that answer specific business questions. Limiting the number of components per dashboard and using reasonable date ranges (e.g., ‘Last 90 Days’ instead of ‘All Time’) reduces the query load and improves load times. This provides a better user experience and is more scalable for a large user base.

In Salesforce Analytics, folders are a primary mechanism for managing security. When you move a dashboard into a folder, it inherits the sharing permissions (View, Manage, etc.) defined at the folder level. This is a powerful feature for bulk administration but requires careful planning of folder structures and permissions.

The most fundamental step is to ensure the underlying field in the Salesforce object has the correct data type (Currency or Number). If the field is a text or other non-numeric type, it cannot be summed in reports or dashboards, regardless of dashboard component settings. This is a common data model issue that an admin must address first.0