Analytics-Admn-201 VCE Exam Download

To force Tableau Server to require the setup of a new administrator account (e.g., resetting the server to an initial setup state), the tsm reset command is the appropriate tool. This command resets Tableau Server’s administrative configuration, including the TSM administrator account, while preserving content like workbooks and data sources.

Option B (Run the tsm reset command): Correct. Running tsm reset clears the current TSM administrator credentials and configuration settings. The next time you access TSM (e.g., via the web interface or CLI), it prompts you to set up a new administrator account, mimicking the initial setup process. Command: tsm reset --username --password .

Option A (Edit tabsvc.yml): Incorrect. The tabsvc.yml file contains service configuration data, but manually editing it is not supported or recommended for resetting the administrator account. It could also corrupt the installation.

Option C (Run the tsm register command): Incorrect. The tsm register command is used to register Tableau Server with a new product key or identity store, not to reset the administrator account.

Option D (Reinstall Tableau Server): Incorrect. Reinstallation wipes the entire server, including content, and is overkill for this task. The tsm reset command achieves the goal without data loss.

Abandoned workbooks—those no longer actively used—can clutter Tableau Server and consume resources (e.g., disk space for extracts). Identifying them efficiently requires leveraging built-in administrative tools rather than manual or destructive methods. Let’s explore this in depth:

Tableau Server Admin Views: Tableau provides pre-built administrative views to monitor server health, usage, and content. The Stale Content view, accessible under Server > Status > Administrative Views, is specifically designed to identify content (workbooks, data sources) that hasn’t been viewed or modified recently. It shows:

Content name, owner, and project.

Last viewed date and last modified date.

View count over a period.This view uses Repository data to track usage metrics, making it ideal for spotting abandoned workbooks.

Option A (Use the Stale Content administrative view): Correct. This is the most efficient and non-invasive method. You can filter by last viewed date (e.g., >30 days ago) to identify workbooks with large extracts that users have stopped accessing. From there, you can contact owners or delete the content if policy allows. It’s a server administrator’s go-to tool for content management.

Option B (Examine extract files in ProgramData/.../extract): Incorrect and impractical. The ProgramData/Tableau/Tableau Server/data/tabsvc/dataengine/extract directory stores .hyper extract files, but:

File names are cryptic (e.g., GUIDs), not tied directly to workbook names.

It doesn’t indicate usage or abandonment—only file presence and size.

Manual inspection is time-consuming and error-prone compared to the Stale Content view.

Option C (Delete all extracts and allow them to be re-generated): Incorrect and risky. Deleting extracts (e.g., via tsm maintenance cleanup) removes them without identifying usage. Regeneration only occurs if a schedule or user triggers it, potentially disrupting active users and losing historical data unnecessarily.

Option D (View all workbooks, and sort by the Modified date): Partially effective but inefficient. In the Tableau Server UI (e.g., under Content > Workbooks), you can sort by "Last Modified," but:

It doesn’t show viewership (a workbook might be modified recently but unused).

It’s manual and doesn’t scale for large deployments compared to the Stale Content view.

Why This Matters: The Stale Content view leverages Tableau’s metadata to provide actionable insights, saving time and reducing risk compared to manual or destructive alternatives. It’s part of Tableau’s governance toolkit.

Tableau Server has specific hardware requirements for production environments to ensure stability and performance. The minimum recommended free disk space for a production installation is 50 GB. This accounts for:

The installation itself (approximately 1–2 GB).

Space for log files, temporary files, and extracts managed by the File Store and Data Engine.

Room for backups and operational overhead.

The full minimum hardware recommendations for a single-node production deployment are:

8 CPU cores (2.0 GHz or faster).

32 GB RAM.

50 GB free disk space (on the system drive, typically C: on Windows).

Option A (32 GB): Incorrect. While 32 GB is the minimum RAM requirement, it’s insufficient for disk space in production.

Option B (50 GB): Correct. This matches Tableau’s official recommendation for production environments.

Option C (15 GB): Incorrect. 15 GB is the minimum for a non-production or trial installation, not production.

Option D (64 GB): Incorrect. While 64 GB exceeds the minimum, it’s not the specified requirement—50 GB is sufficient.

When an extract refresh fails on Tableau Server, troubleshooting requires identifying the root cause—e.g., connectivity issues, resource constraints, or configuration errors. The Backgrounder process handles extract refreshes, so it’s a key focus, but the best diagnostic tool depends on granularity and context. Let’s explore this thoroughly:

Extract Refresh Process:

An extract refresh pulls data from a source (e.g., database, file) into a .hyper file stored on Tableau Server.

The Backgrounder executes these tasks based on schedules or manual triggers.

Errors could stem from: database connectivity, credentials, file access, resource overload, or task misconfiguration.

Option B (Background Tasks for Extracts administrative view): Correct. This is the most direct and detailed method:

Location: In the Tableau Server web UI, go to Server > Status > Background Tasks for Extracts (or site-specific under Site > Status).

Details Provided:

Task name, schedule, and workbook/data source.

Start/end times and status (e.g., Failed, Success).

Error messages (e.g., "Cannot connect to database," "Permission denied").

Why It’s Best: It pinpoints the exact failure (e.g., "timeout," "invalid credentials") for the specific refresh, offering actionable insights without needing to dig through logs manually. Server or site administrators can access this view to diagnose issues quickly.

Example: If the error is "Database login failed," you’d check credentials in the data source settings next.

Option A (Status of the Backgrounder process via tsm status -v): Partially useful but insufficient:

What It Shows: Running/stopped status of all processes (e.g., "Backgrounder: RUNNING").

Limitation: It confirms if Backgrounder is operational but doesn’t reveal why a specific task failed—no error details or task-level granularity.

Use Case: If Backgrounder is stopped or crashed, this might indicate a broader issue, but the question implies a single refresh error, not a server-wide failure.

Option C (The UNC path to the extract’s data source): Relevant but secondary:

Context: If the data source is a file (e.g., CSV on a network share), the UNC path (e.g., \\server\share\file.csv) must be accessible.

Why Not First: The error could be unrelated (e.g., database issue, not file-based). The admin view (B) would reveal if it’s a path issue first, guiding you to check the UNC path only if indicated (e.g., "File not found").

Practical Note: Backgrounder needs share permissions and the Run As account must access it—checking this without context wastes time.

Option D (Whether project permissions are set to Locked): Unlikely cause:

Permissions Impact: Locked permissions restrict who can edit/view content, not whether an extract refresh runs—that’s tied to the data source’s connection settings and Backgrounder execution.

Exception: If the refresh user lacks "Connect" permission to the data source, it might fail, but this is rare (owner/schedule typically has access). The admin view would flag this.

Why This Matters: The Background Tasks view is Tableau’s purpose-built tool for extract diagnostics, saving time and reducing guesswork in production environments.