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

Tableau Services Manager (TSM) is the administrative tool for managing Tableau Server’s configuration, processes, and topology. To log in to TSM (via the web UI at https:// :8850 or CLI), you need:

TSM administrator credentials: These are distinct from site roles and are set during installation or reset via tsm reset.

Local administrative rights: On Windows, the account used to access TSM must be in the local Administrators group on the initial node, as TSM interacts with system-level services.

In a test cluster, the engineer’s inability to log in suggests they lack either the correct TSM credentials or sufficient OS-level permissions. Since the question focuses on a Windows environment and “initial node,” the most immediate requirement is local administrative rights to run TSM commands or access the UI.

Option C (An account with administrative rights to the computer): Correct. The engineer must use an account in the local Administrators group on the initial node to authenticate to TSM. After that, they’ll need the TSM admin username/password set during installation.

Option A (An account with a Creator site role): Incorrect. Site roles (e.g., Creator) apply to content access within Tableau Server, not TSM administration.

Option B (An account with a Site Administrator role): Incorrect. Site Administrators manage site content, not server-level TSM functions.

Option D (An account for the Tableau Server administrator): Partially correct but incomplete. This likely refers to the TSM admin account, but without local admin rights on the machine, login will fail. Option C is more precise.

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.

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.

Single Sign-On (SSO) allows users to authenticate once (e.g., via a corporate identity provider) and access Tableau Server without re-entering credentials. Tableau Server supports several SSO methods:

OpenID Connect (OIDC): An OAuth 2.0-based protocol for SSO, configured via Tableau’s SAML settings with an OIDC-compatible IdP (e.g., Google, Okta).

Kerberos with Active Directory: A ticket-based SSO protocol, widely used in Windows environments with AD integration.

SAML: A flexible SSO standard using XML assertions, supporting various IdPs (e.g., ADFS, PingFederate).

Let’s evaluate:

Option A (OpenID Connect): Correct. OIDC is an SSO method, implemented as a SAML variant in Tableau Server, enabling seamless login.

Option C (Kerberos with Active Directory): Correct. Kerberos provides SSO in AD environments, delegating authentication to the domain controller.

Option D (Security Assertion Markup Language - SAML): Correct. SAML is a core SSO method in Tableau, widely adopted for enterprise integrations.

Option B (Local Authentication): Incorrect. Local Authentication uses Tableau’s internal user database, requiring manual credential entry—no SSO support.

Why This Matters: SSO enhances user experience and security by leveraging existing identity systems, reducing password fatigue.

Tableau Server’s user-based licensing (Creator, Explorer, Viewer) ties licenses to individual users—let’s determine compatible authentication methods:

User-Based Licensing:

Licenses are assigned per user, tracked by username.

Authentication determines how users log in—must integrate with licensing.

Option A (Local authentication): Correct.

Details: Users are managed in Tableau Server’s internal database—username/password set manually or via import.

Why: Directly ties to user accounts, fully compatible with licensing.

Option C (Trusted authentication): Correct.

Details: Allows external apps to authenticate users via tickets (e.g., /trusted/).

Why: Maps to Tableau usernames, integrating with licensing—common for embedded analytics.

Config: Trusted IPs or credentials set in TSM.

Option D (Active Directory): Correct.

Details: Uses AD for authentication (LDAP or Kerberos)—users sync to Tableau Server.

Why: AD usernames align with licensing—supports SSO and user management.

Config: Enable via tsm authentication active-directory configure.

Option B (Reliance authentication): Incorrect.

Why: Not a recognized Tableau authentication method—likely a typo (e.g., for "Resilience" or misheard term). No such feature exists.

Why This Matters: Authentication flexibility ensures user-based licensing fits diverse IT environments—critical for adoption.

Backing up Tableau Server ensures recovery from failures or migrations. A full backup includes multiple data types—let’s dissect this comprehensively:

Backup Components:

Repository Data: PostgreSQL database with metadata (users, permissions, workbooks). Backed up via tsm maintenance backup -f <filename>.tsbak.

Configuration Data: Server settings (e.g., ports, authentication) also in the .tsbak file.

Server Secrets: Encryption keys, internal tokens, Repository passwords—critical for restoring functionality.

Extracts: .hyper files in File Store (optional, separate backup).

Option A (Server secrets and Repository passwords): Correct.

Details: Includes encryption keys (for extracts), internal tokens (process communication), and Repository credentials. Backed up separately or stored securely (e.g., tsm security export-keys).

Why Critical: Without these, restored data may be inaccessible or services may fail.

Option C (Configuration data): Correct.

Details: Ports, authentication settings, process topology—part of the .tsbak file.

Why Critical: Restores server behavior and connectivity post-recovery.

Option D (Repository data): Correct.

Details: Core metadata database—also in .tsbak.

Why Critical: Without it, all content and user data is lost.

Option B (Topology data): Incorrect.

Details: Topology (process distribution) is part of configuration data in the .tsbak, not a separate entity. It’s not distinctly backed up as “topology data.”

Why This Matters: A complete backup (secrets, config, repository) ensures full restoration—missing any piece risks an unusable server.

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:

Version Context: Tableau Desktop 10.5 was released in 2017 and used the .tde (Tableau Data Extract) format for extracts. Tableau Server 2020.1, released in 2020, introduced the .hyper extract format (starting with version 10.5, but fully standardized later). When publishing from an older Desktop version to a newer Server version, Tableau ensures backward compatibility but may upgrade certain components.

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.

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 uses caching to speed up workbook loading by storing query results. After a scheduled extract refresh updates the data, the cache may need recomputing—let’s dive into the mechanics:

Caching Basics:

VizQL Cache: Stores rendered views and query results for faster access.

Refresh Trigger: A scheduled refresh updates the underlying extract (.hyper), but the cache isn’t automatically invalidated—it’s demand-driven.

Recompute Conditions: Tableau recomputes the cache when the workbook is accessed (viewed) and its data has changed (e.g., via refresh).

Evaluation:

Option B (The workbook has upcoming scheduled refresh tasks): Correct.

Why: An upcoming refresh task indicates the workbook relies on an extract with a schedule. After the refresh runs, the data changes, priming the cache for recomputation on next view. Without a schedule, no refresh occurs, so this is a prerequisite.

Detail: Schedules are set in Schedules > Tasks—e.g., "Daily at 2 AM."

Option D (The workbook has been viewed recently): Correct.

Why: Viewing triggers cache recomputation if the data has changed (e.g., post-refresh). Tableau uses a "lazy caching" model—cache updates only when a user loads the workbook, ensuring fresh results.

Detail: "Recently" isn’t strictly defined but implies post-refresh access.

Option A (Published in the last month): Incorrect.

Why: Publish date is irrelevant—cache recomputation ties to data changes and access, not publication timing.

Option C (All Users group has permission rule allowing access): Incorrect.

Why: Permissions enable viewing, but recomputation requires actual access (viewing) and a refresh event, not just potential access.

Why This Matters: Caching balances performance and freshness—understanding triggers prevents stale data surprises.

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.

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.

Comments on visualizations foster collaboration in Tableau Server—let’s break down the requirements:

Commenting Prerequisites:

Site-Level Enablement: Comments must be activated for the site.

Permission: Users need the "Add Comment" capability on the content.

Site Role: Minimum role of Viewer allows commenting if permissions are set.

Option B (Add Comments must be allowed in permissions): Correct.

Details: In the Permissions dialog (e.g., for a workbook), set "Add Comment" to "Allowed" for users/groups. Default is "Denied" unless explicitly enabled.

How: Content > Workbooks > Actions > Permissions > Edit Rule.

Why: Permissions are granular—site enablement alone isn’t enough.

Option D (Comments must be enabled on the site Settings page): Correct.

Details: Go to Site > Settings > General > Allow Comments—check the box.

Why: This is a site-wide toggle (default: off). Without it, no one can comment, regardless of permissions.

Option A (Minimum site role of Explorer - can publish): Incorrect.

Why: Viewer role suffices if permissions allow—Explorer (can publish) isn’t required (it adds publishing, not commenting).

Option C (Server Settings page): Incorrect.

Why: Comments are a site-level feature, not server-wide—no such toggle exists in TSM’s Server Settings.

Why This Matters: Enabling comments at both site and content levels ensures controlled collaboration—key for team insights.

When a user reports slow performance for a newly-published workbook on Tableau Server, troubleshooting requires isolating the cause—e.g., data source issues, server load, workbook design, or caching. The first question should establish a baseline to narrow the scope. Let’s analyze this step-by-step with depth:

Performance Context:

A workbook’s speed depends on:

Data Source: Query complexity, size, network latency (e.g., database vs. extract).

Workbook Design: Filters, calculations, dashboard complexity.

Server Resources: VizQL rendering, Backgrounder load, caching.

"Newly-published" implies it’s not yet optimized or cached on the server.

Option A (Does it run any faster in Tableau Desktop?): Correct.

Why First: Comparing Desktop vs. Server performance is the most foundational diagnostic step:

Desktop Baseline: If it’s slow in Desktop (local machine), the issue likely lies in the workbook (e.g., complex queries, large data) or data source (e.g., slow database)—not Server-specific.

Server Difference: If it’s fast in Desktop but slow on Server, the problem could be server-side (e.g., resource contention, network latency to the data source from Server).

Practical Next Steps:

Slow in Desktop: Optimize workbook (e.g., simplify calcs, use extracts).

Fast in Desktop: Check Server (e.g., caching, VizQL load).

Why Critical: Establishes whether the issue is inherent to the workbook/data or introduced by Server—guides all further investigation.

Option B (Does the workbook always run slowly or does performance vary?): Useful but secondary.

Why Not First: Variability (e.g., slow at peak times) points to server load, but without a Desktop baseline, you can’t rule out workbook design. It’s a follow-up question after A.

Detail: Variability might suggest caching or concurrent user impact, but it assumes Server-side causation prematurely.

Option C (How many times have you opened the workbook in Tableau Server?): Less relevant initially.

Why Not First: Frequency of access might affect caching (first load is slower, subsequent loads faster), but it’s too specific and doesn’t isolate Desktop vs. Server. It’s a niche follow-up.

Option D (Did you enable caching on the workbook?): Misleading and incorrect.

Why Not First: Caching is server-managed (e.g., VizQL cache settings via tsm data-access caching set), not a user-toggle per workbook. Users don’t "enable" it—admins do. Plus, it’s premature without a baseline.

Why This Matters: Starting with Desktop performance cuts through assumptions, pinpointing whether the root cause is client-side (workbook/data) or server-side—essential for efficient resolution in production.