SCA-C01 Dumps with Practice Exam Questions Answers

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.

Tableau Server is designed for production environments and is supported only on server-class operating systems, not desktop operating systems. As of the latest documentation (aligned with knowledge up to March 21, 2025), the supported operating systems for Tableau Server on Windows are:

Windows Server 2016

Windows Server 2019

Windows Server 2022 (added in later versions, but relevant as of 2025).

Desktop operating systems like Windows 7 or Windows 10 are not supported for production installations due to stability, security, and performance requirements.

Option A (Windows 7): Incorrect. Windows 7 is a desktop OS and is not supported for Tableau Server. It’s also end-of-life as of January 2020.

Option B (Windows 10): Incorrect. Windows 10 is a desktop OS and not supported for production Tableau Server deployments, though it may be used for testing in non-production scenarios.

Option C (Windows Server 2019): Correct. This is a supported server OS for Tableau Server.

Option D (Windows Server 2016): Correct. This is also a supported server OS for Tableau Server.

Subscriptions in Tableau Server deliver workbook views to users via email on a schedule. Group subscriptions apply to all group members—let’s unpack this:

Group Subscription Mechanics:

Created viaWorkbooks > Actions > Subscribe > Select Group.

Delivers content to all users in the group at the time the subscription runs (e.g., daily PDF).

Dynamic: Membership updates (additions/removals) are reflected automatically on the next run.

Option C (The subscription updates automatically to include the new user): Correct.

Details: When you add a user to the group (e.g., viaUsers > Groups > Add Users), Tableau Server’s subscription process queries the group’s current membership at runtime. The new user receives the subscription on the next scheduled delivery—no manual action needed.

Example: Group "Sales" has a 9 AM subscription. Add a user at 8 AM—they get the email tomorrow at 9 AM.

Option A (Admin receives notice to approve/deny): Incorrect.

Why: No approval workflow exists for group membership changes in subscriptions—it’s automatic.

Option B (Creator must manually edit): Incorrect.

Why: Subscriptions are tied to the group, not a static user list—manual edits aren’t required for membership changes.

Option D (Only members at creation time): Incorrect.

Why: This would be true for individual subscriptions (static list), but group subscriptions are dynamic.

Why This Matters: Dynamic group subscriptions streamline content delivery as teams evolve, reducing admin overhead.

Data-driven alerts in Tableau Server allow users to receive notifications when data in a view meets certain conditions (e.g., a sales metric exceeds a threshold). By default, this feature is disabled for a site unless explicitly enabled by an administrator.

Option C (Change the data-driven alerts setting on the new site's Settings page): This is the correct answer. In the Tableau Server web interface, a site administrator can navigate to the site’s Settings > General page and enable the option "Let users create data-driven alerts." This must be done manually because the default setting for a new site is disabled. Once enabled, users with appropriate permissions (e.g., Viewer, Explorer, or Creator roles) can create alerts on views they have access to.

Option A (Enable data-driven alerts on the TSM Configuration page): This is incorrect because the TSM Configuration page (accessed via the TSM web UI or CLI) manages server-wide settings like ports, authentication, and processes, not site-specific features like data-driven alerts.

Option B (Run the tsm configuration set -k dataAlerts.checkIntervalInMinutes -v 60 command): This is incorrect. The dataAlerts.checkIntervalInMinutes key controls how frequently Tableau Server checks alert conditions (default is 60 minutes), but it does not enable the feature itself. The feature must first be turned on at the site level.

Option D (No action is necessary): This is incorrect because the default setting for data-driven alerts is off for new sites, requiring explicit action to enable it.

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.