Tableau Tableau Server Certified Associate Exam SCA-C01 Exam Dumps: Updated Questions & Answers (July 2025)

In Tableau Server,projectsare containers for organizing and securing content. They help manage permissions and structure content hierarchically. Let’s define what can be contained:

Workbooks: Visualizations and dashboards published to the Server.

Data Sources: Published connections or extracts reusable across workbooks.

Nested Projects: Sub-projects within a parent project, introduced in later versions (e.g., 2018.2) for deeper organization.

Option B (Workbooks): Correct. Workbooks are the primary content type in projects, containing views and dashboards.

Option C (Nested Projects): Correct. Nested projects allow hierarchical structuring (e.g., a "Sales" project with "Q1" and "Q2" sub-projects), with inherited or custom permissions.

Option D (Data Sources): Correct. Published data sources reside in projects, providing reusable data connections.

Option A (Groups): Incorrect. Groups are collections of users managed at the site or server level, not stored within projects. Projects contain content, not user entities.

Why This Matters: Projects are key to content governance—knowing what they hold helps administrators organize and secure assets effectively.

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.

Tableau Server uses a role-based licensing model with three primary license levels: Creator, Explorer, and Viewer. Each license level corresponds to specific site roles that define what users can do on the server.

Viewer License: This is the most restrictive license, allowing users to view and interact with published content (e.g., dashboards and visualizations) but not to create or publish new content.

Site Role: The Viewer license can only be associated with the Viewer site role. This role restricts users to viewing capabilities, aligning with the license’s purpose.

Option A (Creator): Incorrect. The Creator license is for users who can create, edit, and publish content using Tableau Desktop and the web interface. It corresponds to the Creator site role, not Viewer.

Option B (Explorer (can publish)): Incorrect. This is a variation of the Explorer license, which allows users to edit and publish content within limits. It’s more permissive than Viewer.

Option C (Viewer): Correct. The Viewer site role matches the Viewer license level perfectly.

Option D (Explorer): Incorrect. The Explorer license allows users to explore data and create content in the web interface, exceeding the Viewer license’s capabilities.

Tableau Server’s minimum hardware recommendations for a production single-node deployment ensure reliable performance for small to medium workloads. As of the latest documentation:

CPU: 8 cores (2.0 GHz or higher) to handle concurrent users, rendering, and background tasks.

RAM: 32 GB to support in-memory processing (e.g., VizQL, Data Engine) and caching.

Disk Space: 50 GB free for installation, logs, extracts, and temporary files.

Let’s break it down:

Option C (8-Core CPU, 32 GB RAM, 50 GB free disk space): Correct. This matches Tableau’s official minimum for production:

8 cores ensure sufficient parallelism for processes like Backgrounder and VizQL.

32 GB RAM supports multiple users and extract refreshes.

50 GB disk space accommodates growth (initial install is ~1–2 GB, but logs and extracts expand).

Option A (4-Core, 16 GB RAM, 50 GB): Incorrect. Too low for production—4 cores and 16 GB RAM are below the threshold for reliable performance under load.

Option B (2-Core, 8 GB RAM, 15 GB): Incorrect. This is for non-production (e.g., trial) setups, insufficient for production stability.

Option D (4-Core, 64 GB RAM, 50 GB): Incorrect. 4 cores are inadequate, though 64 GB RAM exceeds the minimum (32 GB).

Why This Matters: Under-spec hardware can lead to slow performance, failed refreshes, or crashes in production—adhering to the minimum ensures stability.

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., underContent > 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.

When an extract refresh fails on Tableau Server, troubleshooting requires identifying the root cause—e.g., connectivity issues, resource constraints, or configuration errors. TheBackgrounderprocess 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 toServer > Status > Background Tasks for Extracts(or site-specific underSite > 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.

Tableau Server relies on several processes to function, each with a specific role. TheRepositoryprocess (powered by PostgreSQL) serves as the database for metadata, storing critical information such as:

User and group details.

Permissions and site configurations.

Workbook and data source metadata (e.g., schedules, subscriptions).

Option B (Repository): Correct. The Repository is the centralized database that holds all metadata, making it the backbone of Tableau Server’s content management. There are typically two instances in an HA setup (one active, one passive), monitored by the Cluster Controller.

Option A (Data Engine): Incorrect. The Data Engine manages in-memory data processing and extract storage (e.g., .hyper files), not metadata. It’s separate from the Repository.

Option C (Backgrounder): Incorrect. The Backgrounder handles background tasks like extract refreshes and subscriptions, but it doesn’t store metadata—it interacts with the Repository to retrieve task details.

Option D (File Store): Incorrect. The File Store manages physical extract files and workbook assets, not metadata, which is stored in the Repository.

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. TheStale Contentview, accessible underServer > 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., underContent > 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 uses internal secrets (tokens) for secure communication between its processes (e.g., Repository, File Store). These are automatically generated during installation and can be regenerated if compromised or for security maintenance. The command to update these is:

tsm security regenerate-internal-tokens: This regenerates the internal security tokens, ensuring all processes use the new tokens after a restart.

Option C (tsm security regenerate-internal-tokens): Correct. This is the documented command for updating internal secrets.

Option A (tsm data-access caching set -r 1): Incorrect. This command configures caching behavior, not security tokens.

Option B (tsm licenses refresh): Incorrect. This refreshes license data, unrelated to internal secrets.

Option D (tsm security validate-asset-keys): Incorrect. This validates encryption keys for assets, not internal tokens.