Analytics-Admn-201 Salesforce Certified Tableau Server Administrator Questions and Answers

In Tableau, data sources can be embedded (stored within a workbook) or published (stored separately on Tableau Server). Let’s define these and analyze the advantages:

Embedded Data Source: The connection details and any extract are bundled in the .twb or .twbx file. Each workbook manages its own copy.

Published Data Source: The connection or extract is hosted on Tableau Server, reusable across multiple workbooks.

Now, let’s evaluate the options:

Option C (Centralized data management is easier): Correct. Published data sources allow:

Single source of truth: One data source can serve multiple workbooks, ensuring consistency.

Unified updates: Refresh schedules, permissions, and metadata (e.g., calculated fields) are managed in one place via the Server UI.

Governance: Administrators can control access and monitor usage centrally.In contrast, embedded data sources require individual updates per workbook, leading to duplication and management overhead.

Option D (Storage space is conserved and resource usage during data refreshes is optimized): Correct. With published data sources:

Storage: A single extract on the Server (e.g., a .hyper file) is shared across workbooks, avoiding redundant copies stored in each embedded workbook.

Refreshes: One refresh job updates the shared extract, reducing CPU and memory usage compared to multiple refreshes for duplicate embedded extracts.Embedded data sources replicate extracts, increasing disk space and refresh load.

Option A (Data is protected so that it is only available in one workbook): Incorrect. This describes embedded data sources, not published ones. Published data sources are shared, not restricted to one workbook—permissions control access, not exclusivity.

Option B (Drivers are automatically installed on each client's machine): Incorrect. Drivers (e.g., for SQL Server, PostgreSQL) must be installed on the Server hosting the published data source, not client machines. This is unrelated to the published vs. embedded distinction.

Why This Matters: Published data sources enhance scalability and efficiency in enterprise deployments, making them a cornerstone of Tableau Server’s data strategy.

Editing permissions on a workbook in Tableau Server depends on the user’s role and the project’s permission settings. Since permissions are not locked (i.e., "Managed by Owner"), let’s dissect who can edit them:

Permission Model:

Not Locked: Owners of content (workbooks, data sources) can set permissions, and Project Leaders can override at the project level.

Site Roles: Define maximum capabilities (e.g., Viewer, Explorer, Creator).

Capabilities: "Set Permissions" is explicit—only certain users get it.

Option C (The workbook’s owner): Correct.

Details: The owner (typically the publisher) has full control over their workbook when permissions are Managed by Owner:

How: In the UI, go to Content > Workbooks > Actions > Permissions—owners can edit rules (e.g., grant Editor to a group).

Site Role: Minimum of Explorer (can publish) or Creator to publish, ensuring "Set Permissions" capability.

Why: Ownership inherently includes permission management unless locked.

Option D (Users set to Project Leader for the workbook’s project): Correct.

Details: Project Leaders are assigned via Content > Projects > Actions > Permissions > Set Project Leader:

Power: Can edit permissions for all content in the project, even if not the owner.

Site Role: Requires Site Administrator or Server Administrator (Creator/Explorer variants suffice).

Why: Overrides ownership in Managed by Owner mode—ensures project-level governance.

Option A (Users with project and workbook Viewer role): Incorrect.

Why: Viewer role (site-level) limits users to viewing—lacks "Set Permissions" capability, regardless of project/workbook rules.

Option B (Users with workbook Interactor role): Incorrect.

Why: "Interactor" isn’t a standard role—likely a misnomer for Explorer or Viewer with interaction permissions (e.g., Filter). No permission-editing rights exist here.

Why This Matters: Knowing who can edit permissions prevents access control gaps—crucial for collaborative or regulated environments.

In an HA Tableau Server cluster, the Coordination Service (ZooKeeper ensemble) maintains cluster state—let’s find the best way to check it:

Coordination Service:

Runs on multiple nodes (3 or 5 in HA) to ensure quorum and failover.

Status indicates if it’s running and synced—critical for cluster health.

Option C (Run tsm status -v): Correct.

Details: tsm status --verbose lists all processes across nodes, including Coordination Service (e.g., "Coordination Service: RUNNING").

Why Best: Provides detailed, node-specific status in the CLI—e.g., "Node 1: RUNNING, Node 2: RUNNING."

Use: Run on the initial node; -v ensures full output.

Option A (TSM web client Status page): Incorrect.

Why: The TSM UI (Server > Status) shows process counts (e.g., "Coordination Service: 3 instances"), but not detailed per-node status—less granular than CLI.

Option B (tsm maintenance ziplogs): Incorrect.

Why: Generates log archives for troubleshooting, not a real-time status check.

Option D (Tableau Server Status page): Incorrect.

Why: The Server Status page (Server > Status in the web UI) monitors application processes (e.g., VizQL), not TSM’s Coordination Service.

Why This Matters: Coordination Service health ensures HA stability—tsm status -v is the admin’s go-to for precision.

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.

Data-driven alerts notify users when data meets conditions (e.g., sales > $10K). Let’s examine when Tableau checks these:

Alert Mechanics:

Enabled per site (Settings > General > Data-Driven Alerts).

Backgrounder evaluates conditions against extract data.

Check Intervals: Configurable via tsm configuration set -k dataAlerts.checkIntervalInMinutes (default: 60 minutes).

Refresh Trigger: Also checks post-extract refresh for immediate updates.

Option A (Every 60 minutes): Correct.

Details: Default interval—Backgrounder polls every hour to evaluate alert conditions.

Config: Adjustable (e.g., -v 30 for 30 minutes).

Option D (Whenever extracts in the related workbook are refreshed): Correct.

Details: An extract refresh updates the data, triggering an immediate alert check to catch changes promptly.

Why: Ensures timely notifications without waiting for the next poll.

Option B (Every 10 minutes): Incorrect.

Why: Not the default—possible via config, but not standard.

Option C (Whenever a new extract is published): Incorrect.

Why: Publishing creates the extract; alerts trigger on refreshes or polling, not initial publication.

Why This Matters: Timing affects alert responsiveness—balancing frequency and server load is key.

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.

Installing Tableau Server on Windows requires an account with sufficient privileges to configure services, write to the file system, and manage registry settings. Let’s analyze this in depth:

Installation Requirements:

The installer creates services (e.g., Tableau Server Gateway), writes to Program Files and ProgramData, and configures TSM.

It needs local administrative privileges on the machine to perform these tasks.

Post-install, a "Run As" account can be set for services (e.g., NT AUTHORITY\NetworkService), but this is separate from the install account.

Option C (An account in the local administrator group): Correct.

Why: The account must be in the local Administrators group to:

Install software (UAC elevation).

Configure services and ports.

Write to protected directories (e.g., C:\Program Files\Tableau).

Examples: A local admin (e.g., Administrator) or a domain user added to the Administrators group (e.g., DOMAIN\AdminUser).

Process: Log in as this account, run the installer, and provide TSM admin credentials during setup.

Option A (A local user account): Incorrect.

A standard local user (not in Administrators) lacks permissions—installation would fail with "Access Denied" errors.

Option B (A domain user account): Incorrect unless clarified.

A domain user without local admin rights can’t install. If it’s in the Administrators group, it qualifies, but C is more specific.

Option D (NT AUTHORITY\NetworkService): Incorrect.

This is a built-in service account for running services (default "Run As" post-install), not for executing the installer—an interactive user account is required.

Why This Matters: Using the right account prevents install failures and ensures secure configuration—critical for production setups.

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 installer configures process instances based on hardware and deployment type (single-node vs. multi-node). For a single-node installation with 4 cores, we need to consider the default process topology. Let’s break this down exhaustively:

Key Processes:

Gateway: Handles incoming requests (1 instance).

Application Server (VizPortal): Manages UI and sessions (1 instance).

VizQL Server: Renders visualizations (2 instances).

Backgrounder: Runs extract refreshes, subscriptions (1 instance).

Data Server: Manages data connections (1 instance).

File Store: Stores extracts (1 instance).

Repository: Metadata database (1 instance, active).

Cluster Controller, Cache Server, etc.: Supporting processes (typically 1 each).

Default Configuration:

On a single-node install, Tableau sets 1 instance per process unless specified otherwise, except for VizQL, which defaults to 2.

The installer doesn’t scale instances linearly with cores (e.g., 4 cores ≠ 4 instances). Post-install, TSM can adjust this (e.g., tsm topology set-process), but the question asks for the installed default.

Minimum hardware (8 cores, 32 GB RAM) suggests higher defaults, but 4 cores still triggers a minimal setup.

Option B (1): Correct with Caveat.

Most processes (e.g., Backgrounder, Gateway, Data Server) default to 1 instance on install, regardless of 4 cores.

VizQL defaults to 2, but the question’s phrasing ("each process") implies a general rule. Historically (and per docs), 1 is the baseline for most, with VizQL as the exception.

Interpretation: Assuming "each" means the typical case, 1 fits most processes on a 4-core single-node setup.

Option A (2): Incorrect. Only VizQL defaults to 2; others don’t.

Option C (8): Incorrect. Far exceeds defaults—8 cores might justify more, but not 4.

Option D (4): Incorrect. Not tied to core count by default; manual config would be needed.

Why This Matters: Understanding defaults aids capacity planning—4 cores is below production minimum (8), so performance tuning may be needed post-install.

In Tableau Server, schedules manage tasks like extract refreshes and subscriptions. Each task within a schedule has a priority value (ranging from 1 to 100, where 1 is the highest priority and 100 is the lowest). Tasks with higher priority (lower numbers) are executed before tasks with lower priority (higher numbers) when queued by the Backgrounder process. If the Backgrounder is overloaded or delayed, lower-priority tasks may not complete on time, leading to inconsistent refreshes.

In this scenario:

The 7:00 AM Extract Refresh task is critical for the CEO’s workbook, but the data is only refreshed 70% of the time by 9:00 AM.

The server has a single node, meaning a single Backgrounder process handles all tasks. With five schedules (some overlapping in the early morning), contention or delays could prevent the 7:00 AM task from completing reliably before 9:00 AM.

Option C (Set the priority of this task to 1): Correct. Setting the task priority to 1 ensures it has the highest priority among all queued tasks. This increases the likelihood that the Backgrounder executes it promptly at 7:00 AM, completing the refresh before the CEO accesses the workbook at 9:00 AM. You can adjust task priority in the Tableau Server web interface under Schedules > Tasks > Edit Priority.

Option A (Set the default priority of this schedule to 50): Incorrect. The default priority for schedules is already 50, and this option refers to the schedule’s default, not the specific task. It wouldn’t address the contention issue.

Option B (Set the priority for all other tasks to 50): Incorrect. This keeps all tasks at the default priority (50), leaving the 7:00 AM task without a relative advantage. It doesn’t prioritize the CEO’s task.

Option D (Set the priority of this task to 100): Incorrect. Priority 100 is the lowest, which would deprioritize the task, making the refresh even less reliable.

Tableau Server relies on several processes to function, each with a specific role. The Repository process (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.

The VizQL Server process in Tableau Server handles rendering visualizations and processing queries for users viewing dashboards or workbooks. During installation, Tableau Server automatically configures the number of VizQL instances based on the number of processor cores on the machine, following this rule:

Default VizQL instances = 2 per node, unless manually adjusted post-installation.

In multi-node setups, additional instances may be added based on core count, but the question specifies a single server with 16 cores.

The installer does not scale VizQL instances linearly with core count by default (e.g., it doesn’t set 1 instance per 4 cores). Instead:

For a single-node installation, the default is 2 VizQL instances, regardless of core count (assuming the minimum hardware requirements are met: 8 cores, 32 GB RAM).

Administrators can later adjust this using TSM (e.g., tsm topology set-process) based on performance needs, but the question asks for the default configured by the installer.

Option A (4): Incorrect. Four instances might be configured manually for a 16-core server, but it’s not the default.

Option B (6): Incorrect. Six instances exceed the default for a single node.

Option C (10): Incorrect. Ten instances are far beyond the default and would require manual configuration.

Option D (2): Correct. The installer sets 2 VizQL instances by default on a single-node installation.

In Tableau Server, projects organize content (workbooks, data sources) and use permissions to control access. "Locking permissions" restricts how permissions are managed within a project—let’s explore this exhaustively:

Permission Management Modes:

Managed by Owner: Default mode. Content owners (e.g., workbook publishers) can set permissions on their items, inheriting project defaults as a starting point.

Locked to the Project: Project-level permissions are enforced, and content owners cannot modify them. This ensures consistency across all items in the project.

How to Lock:

In the Tableau Server web UI:

Go to Content > Projects.

Select a project, click Actions > Permissions.

In the Permissions dialog, change Permissions Management from "Customizable" (Managed by Owner) to "Locked."

Set the desired permissions (e.g., Viewer, Editor) for users/groups, which then apply uniformly to all content.

Via REST API: Use the updateProject endpoint with "permissionsLocked": true.

Option B (You can lock permissions to a project by changing Customizable to Locked): Correct.

Details: This is the precise action in the UI—switching from "Customizable" to "Locked" locks permissions at the project level.

Impact: Owners lose the ability to override permissions on individual workbooks/data sources, enforcing governance.

Example: Set "All Users" to Viewer (Locked)—all content in the project is view-only, regardless of owner intent.

Option A (Locking permissions must be enabled on the Server Settings page): Incorrect.

Why: Locking is a per-project setting, not a server-wide toggle. The Server Settings page (via TSM) controls global configs (e.g., authentication), not project permissions.

Option C (Content permissions are locked by default): Incorrect.

Default: New projects are "Managed by Owner" (Customizable), allowing flexibility unless explicitly locked by an admin.

Option D (By setting the appropriate Project permission role): Incorrect.

Confusion: "Project permission role" isn’t a term—permissions are set via rules (e.g., Viewer, Editor), but locking is a separate action (Customizable → Locked).

Why This Matters: Locking permissions ensures uniform access control, critical for regulated environments or large teams where consistency trumps flexibility.