Pass the Tableau Desktop Certified Associate SCA-C01 Questions and answers with ExamsMirror

Tableau Server can record performance metrics for workbooks to troubleshoot slow-loading views. This feature must be enabled at the site level (viaSettings > General > Allow Performance Recording). Once enabled, you can trigger recording for a specific view by modifying its URL.

The correct syntax is to append :record_performance=yes& to the view URL, immediatelyafter the session ID. For example:

Original URL: http://server/#/site/my-site/views/workbook/view?:iid=1

Modified URL: http://server/#/site/my-site/views/workbook/view?:iid=1:record_performance=yes &

After loading the view with this parameter, a performance recording is generated and accessible via thePerformanceoption in the toolbar.

Option B (Type :record_performance=yes& at the end of the view URL, immediately after the session ID): Correct. This follows Tableau’s documented method for enabling performance recording.

Option A (Click the Performance link in the toolbar): Incorrect. The Performance link appears only after recording is triggered via the URL; it’s not the method to enable it.

Option C (Type :record_performance=yes& immediately before the session ID): Incorrect. The parameter must follow the session ID (e.g., :iid=1) to function correctly.

Option D (Delete the session ID in the URL and reload the view): Incorrect. The session ID is required for the view to load properly; removing it breaks the URL.

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 inSchedules > 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.

When Tableau Server uses Active Directory (AD) for authentication, group synchronization imports AD groups and assigns aminimum site role(e.g., Viewer, Explorer) to users in that group. This ensures users meet a baseline access level. The behavior for existing users during sync is:

If the user’s current site role providesmore accessthan the minimum (e.g., Explorer vs. Viewer), their roleremains unchanged.

If the user’s current role providesless accessthan the minimum (e.g., Unlicensed vs. Viewer), their role isupgradedto the minimum.

This preserves higher privileges while enforcing a floor. “Reduces access” means the minimum role is lower than the current role (e.g., Viewer vs. Explorer), in which case the existing role stays.

Option A (It will change to the minimum site role only if the minimum site role reduces access): Correct. The user’s role changes only if the minimum increases access (e.g., Unlicensed to Viewer); otherwise, it stays higher.

Option B (It will change only if the minimum provides more access): Incorrect wording. This is the inverse of the actual behavior—change occurs when needed to meet the minimum, not to exceed it.

Option C (It will always change): Incorrect. Existing higher roles are preserved.

Option D (It will never change): Incorrect. It changes if the current role is below the minimum.

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.

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) duringpublishing. 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 supports multiple authentication methods, including Local Authentication, Active Directory, Kerberos, SAML, and OpenID Connect.OpenID Connect (OIDC)is an identity layer built on OAuth 2.0, commonly used for single sign-on (SSO). In Tableau Server, OIDC is implemented as a variant ofSAML(Security Assertion Markup Language) authentication because both are SSO protocols managed through the same configuration workflow.

To use OpenID Connect:

Configure Tableau Server for SAML/SSO.

Provide an OIDC-compatible identity provider (IdP) configuration (e.g., Google, Okta).

Set up the IdP metadata and certificates in TSM.

Option D (SAML): Correct. Tableau Server treats OIDC as a subset of its SAML authentication framework, so you configure it under the SAML settings in TSM.

Option A (Local Authentication): Incorrect. Local Authentication uses Tableau’s internal user database, not an external SSO protocol like OIDC.

Option B (Kerberos): Incorrect. Kerberos is a network authentication protocol for Windows environments, unrelated to OIDC.

Option C (Active Directory): Incorrect. AD uses LDAP or Kerberos, not OIDC, for authentication.

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. Thefirst questionshould 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.

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.

Editing permissions on a workbook in Tableau Server depends on the user’s role and the project’s permission settings. Since permissions arenot 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 toContent > 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 viaContent > 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.