Publish and Manage Content on Tableau Server and Tableau Cloud

An analyst publishes a daily sales dashboard to Tableau Cloud and wants to be emailed automatically whenever a specific KPI tile shows that total revenue drops below 50,000 for the day. Which Tableau feature should the analyst configure to achieve this?

• AA scheduled subscription that emails the whole dashboard every morning
• BA custom view saved with a filter applied to the revenue figure
• CA workbook permission rule granting the analyst download access to the data
• DA data-driven alert set on the revenue measure with a threshold conditioncheck_circle Correct

Why A is wrong: A subscription delivers the view on a fixed time schedule regardless of the data, so it would email the dashboard daily even when revenue is healthy, which is not the conditional behaviour requested.

Why B is wrong: A custom view only stores a personalised filter and sort state of the dashboard; it never triggers a notification, so it cannot tell the analyst when a value crosses a threshold.

Why C is wrong: Permission rules control what users may view or download and have no notification capability, so granting download access does nothing to alert the analyst when revenue drops.

Why D is correct: A data-driven alert monitors a continuous numeric axis on a published view and sends email when the value crosses a defined threshold, which exactly matches the requirement to be notified when revenue falls below 50,000.

While setting up a refresh schedule for a large extract on Tableau Server, an analyst sees options for a full refresh and an incremental refresh. What does choosing an incremental refresh do to the extract on each scheduled run?

• AIt adds only rows newer than the highest value of a chosen key column, leaving existing rows in place.check_circle Correct
• BIt rebuilds the entire extract from scratch every time so all historical rows are reloaded.
• CIt removes the oldest rows from the extract to keep its total size capped at a fixed limit.
• DIt pauses the schedule until a column changes, then refreshes only the changed cells in place.

Why A is correct: Incremental refresh appends rows whose key column value exceeds the last recorded maximum, so only new records are pulled while existing extract rows stay, which is the defining behaviour.

Why B is wrong: Rebuilding everything from scratch describes a full refresh, not an incremental one, so this confuses the two refresh types the analyst is choosing between.

Why C is wrong: Incremental refresh adds new rows and does not automatically prune old ones, so describing it as a size cap that deletes the oldest data misstates its behaviour.

Why D is wrong: Incremental refresh is driven by a chosen key column at each scheduled run, not by waiting for cell-level changes, so this invents a trigger Tableau does not use.

When an extract refresh schedule is applied to a published data source rather than to an individual workbook, what is the effect on workbooks that connect to that published data source?

• AEach connected workbook must still have its own separate refresh schedule attached to receive updated data.
• BOne scheduled refresh of the published data source updates the data for every workbook that connects to it.check_circle Correct
• CThe schedule refreshes only the first workbook that was published against the data source.
• DThe schedule converts each connected workbook to a live connection so no refresh is needed.

Why A is wrong: This describes per-workbook scheduling, which is what publishing a shared data source avoids; the workbooks inherit the refreshed data without their own schedules.

Why B is correct: Refreshing the shared published data source updates its extract once, and all connected workbooks read from that single refreshed source, so one schedule serves them all.

Why C is wrong: The schedule belongs to the data source, not to any one workbook, so there is no notion of refreshing only the first consumer.

Why D is wrong: Scheduling a refresh does not change the connection type; the data source remains an extract that is periodically refreshed, so this is incorrect.

A workbook owner grants the Marketing group the View permission on a dashboard but explicitly denies them the Download Full Data capability, while leaving the All Users group set to allow that same capability. A marketing analyst who belongs to both groups tries to export the full data and finds the option blocked. Why is the analyst denied despite the All Users allow setting?

• APermissions from the most recently edited group win, so whichever group rule was saved last decides the outcome for the overlapping capability.
• BThe All Users allow only applies to users who have no other group membership, so belonging to Marketing removes the analyst from the All Users rule entirely.
• CDownload Full Data can never be granted to a non-owner, so the All Users allow had no effect and the capability was always going to be blocked.
• DAn explicit Deny on a capability takes precedence over an Allow from any other group, so the Marketing deny overrides the All Users allow for that analyst.check_circle Correct

Why A is wrong: Tempting because edit order sounds plausible, but Tableau does not resolve conflicts by recency; an explicit Deny beats an Allow regardless of when each was set.

Why B is wrong: Tempting because group exclusivity sounds tidy, but a user is evaluated against every group they belong to, and the deny wins through conflict resolution rather than through being dropped from All Users.

Why C is wrong: Tempting because data download feels sensitive, but the capability can be granted to non-owners, and the actual cause here is the explicit Deny overriding the Allow.

Why D is correct: Correct: in Tableau's permission evaluation a specific Deny wins over an Allow granted through another group membership, so the analyst is blocked.

An analyst has built a workbook in Tableau Desktop that connects directly to a local Excel file saved on their laptop. They want to publish the workbook to Tableau Cloud so colleagues can view it without the analyst's laptop being switched on. What should the analyst do during publishing to make the data available to other users?

• APublish the workbook with the connection left as a live connection to the local Excel file path.
• BExport the workbook as a packaged PDF and email that file to each colleague instead.
• CPublish the workbook and rely on Tableau Cloud automatically uploading the Excel file from the laptop later.
• DInclude an extract of the Excel data in the published workbook so the data travels to Tableau Cloud.check_circle Correct

Why A is wrong: A live connection to a local file path is only reachable from the analyst's own machine, so colleagues on Tableau Cloud would see an error when the laptop is off; this is the very problem the analyst is trying to avoid.

Why B is wrong: A PDF export produces a static document rather than an interactive published workbook on Tableau Cloud, so it does not meet the goal of giving colleagues a live, viewable workbook on the site.

Why C is wrong: Tableau Cloud never reaches back into a user's laptop to fetch local files on its own, so this imagined automatic upload does not exist and the data would remain unavailable to colleagues.

Why D is correct: Including an extract embeds a snapshot of the Excel data inside the published workbook, so it lives on Tableau Cloud and remains available to colleagues regardless of whether the analyst's laptop is switched on.