Salesforce Certified Tableau Server Administrator Analytics-Admn-201 Exam Questions

Answer : B

Answer : A

Tableau Server's performance and stability depend on dedicated resources and proper configuration. Running additional software on the same server is the most likely to cause problems because:

Resource contention: Tableau Server requires significant CPU, RAM, and disk I/O. Other software (e.g., databases, web servers) can compete for these resources, leading to slowdowns, crashes, or failed tasks.

Port conflicts: Tableau uses specific ports (e.g., 80, 443, 8850), and other applications might interfere.

Security risks: Additional software increases the attack surface, potentially compromising Tableau Server.

Tableau recommends running the server on dedicated hardware without unrelated applications.

Option A (Running additional software on the server): Correct. This is a common cause of performance issues and is explicitly discouraged in Tableau's best practices.

Option B (Separating the Backgrounder and VizQL processes to different machines): Incorrect. This is a supported multi-node configuration that can improve performance, not cause problems, if properly set up via TSM.

Option C (Configuring the server to use a static IP address): Incorrect. A static IP is recommended for Tableau Server to ensure consistent network access, so it's unlikely to cause issues.

Option D (Using a non-default installation path): Incorrect. While not default, a custom path is supported (via TSM or installer options) and unlikely to cause problems if permissions and disk space are adequate.

Answer : B, C

Comments on Tableau Server visualizations facilitate collaboration. Let's explore what's supported:

Comments Feature: Enabled per site (Settings > General > Allow Comments). Users with 'Add Comment' permission can post on views.

Option B (Text): Correct.

Details: The primary content type---users type free-form text in the comment box.

Use: Notes, questions, or feedback (e.g., 'Sales spiked here---why?').

Option C (@mentions): Correct.

Details: Typing @username notifies the mentioned user via email or the UI (if notifications are enabled).

Use: Directs comments to specific people (e.g., '@John, check this trend').

Option A (Interactive snapshots of a view): Incorrect.

Details: Snapshots (static images) aren't supported in comments---users must take screenshots externally and can't embed them interactively.

Option D (Images - jpg, png): Incorrect.

Details: No attachment or image embedding in comments---text and mentions only. Workaround: Link to an image hosted elsewhere.

Why This Matters: Comments enhance teamwork, but their simplicity (text + mentions) keeps the interface lightweight and focused.

Answer : A

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.

Answer : D

Tableau Server's search functionality relies on an indexed catalog of content (workbooks, data sources, etc.) stored in the Repository. If a user can see a workbook in the UI (e.g., under Content > Workbooks) but not find it via search, the search index may be outdated or corrupted. This can happen due to:

Indexing delays after publishing.

Server maintenance or crashes affecting the index.

Option D (Run the tsm maintenance reindex-search command): Correct. This command rebuilds the search index, ensuring all content (including the user's workbook) is properly cataloged and searchable. Steps:

Stop Tableau Server (tsm stop).

Run tsm maintenance reindex-search.

Start Tableau Server (tsm start).

This is a server administrator task and resolves systemic search issues.

Option A (Re-publish the workbook with keywords): Incorrect. Re-publishing might update the index for that workbook, but it doesn't fix a broader indexing problem. Keywords enhance relevance, not indexing itself.

Option B (Add tags to the workbook): Incorrect. Tags improve searchability but don't address an index failure. If the workbook isn't indexed, tags won't help.

Option C (Log out, and then log back in): Incorrect. This refreshes the user session but doesn't affect the server-side search index.

Why This Matters: A reliable search index is critical for content discovery in large deployments---reindex-search ensures consistency.

Answer : A

In a high-availability (HA) Tableau Server setup, the Repository (PostgreSQL) has an active and passive instance. Failover occurs if the active Repository fails. Let's dive into the process:

HA Setup:

Two Repository instances across nodes (active/passive).

Failover switches to the passive instance if the active one becomes unavailable (e.g., crash, network issue).

Cluster Controller:

Role: Monitors all processes (e.g., Repository, File Store) across nodes, detecting failures via heartbeats and status checks.

Failover Decision: If the active Repository stops responding, Cluster Controller initiates failover, promoting the passive instance to active.

Coordination: Works with Coordination Service (ZooKeeper) to update topology but makes the initial detection call.

Option A (Cluster Controller): Correct.

Why: It's the watchdog process, constantly monitoring Repository health and triggering failover when needed.

Option B (Coordination Service): Incorrect.

Role: ZooKeeper maintains cluster state and coordinates topology updates post-failover, but doesn't detect the failure---Cluster Controller does.

Option C (Gateway): Incorrect.

Role: Routes client requests---unrelated to internal process monitoring or failover.

Option D (Backgrounder): Incorrect.

Role: Executes background tasks---no involvement in Repository failover decisions.

Why This Matters: Understanding failover ensures HA reliability---Cluster Controller is the linchpin for resilience.

Answer : C

Tableau Desktop and Tableau Server have versioning considerations when publishing content, particularly regarding compatibility between older Desktop versions (e.g., 10.5) and newer Server versions (e.g., 2020.1). Let's break this down step-by-step:

Publishing Process: With a Creator site role and Publisher permissions, you have the rights to publish workbooks to the specified project. Tableau Server accepts workbooks from older Desktop versions (e.g., 10.5) and upgrades them to the current Server version (2020.1) during publishing. This process is seamless for the workbook itself, but extracts require special handling.

Extract Handling: If the workbook contains embedded .tde extracts (stored within the .twb or .twbx file), Tableau Server 2020.1 converts these to .hyper format upon publishing. This conversion is necessary because .hyper replaced .tde as the default extract engine starting in Tableau 10.5 and beyond, offering better performance and scalability. During this process, Tableau Desktop or Server displays a warning to inform the user of the upgrade, as it's a one-way conversion (you can't revert to .tde on the Server).

Now, let's evaluate the options:

Option A (You will successfully publish without any errors or warnings): Incorrect. While the publishing succeeds, a warning about the .tde to .hyper conversion appears if the workbook contains embedded extracts. Without extracts, no warning occurs, but the question's context implies extracts are likely involved (common in visualizations).

Option B (Error message: unable to publish to a newer version): Incorrect. Tableau supports publishing from older Desktop versions to newer Server versions. There's no outright error blocking this; compatibility is maintained.

Option C (Warning: embedded .tde extracts will be upgraded to .hyper): Correct. This is the precise warning displayed when a workbook with .tde extracts is published to a Server version that uses .hyper. It ensures the user is aware of the format change, which might affect extract refresh schedules or performance expectations.

Option D (Warning: workbook will be upgraded to a new version): Partially correct but less specific. The workbook is upgraded to 2020.1 compatibility, but the warning focuses on the extract format change (.tde to .hyper), not the workbook version generically. Option C is more accurate.

Why This Matters: The .tde to .hyper shift improves query performance and supports larger datasets, but users need to know about it for planning (e.g., extract refresh schedules might need adjustment). The warning ensures transparency.