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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Tableau Server Architecture and Fundamentals | 20% | - Server components and topology
|
| Topic 2: Day-to-Day Administration | 24% | - Content management
|
| Topic 3: Migration and Upgrade | 15% | - Upgrade procedures
|
| Topic 4: Troubleshooting and Monitoring | 15% | - Monitoring and logging
|
| Topic 5: Installation and Configuration | 26% | - Identity and security integration
|
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NEW QUESTION # 69
What two events must occur for Tableau Server to recompute queries for a workbook cache after a scheduled refresh? (Choose two.)
Answer: A,C
Explanation:
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).
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.
NEW QUESTION # 70
You are the server administrator of a single-node Tableau Server installation. The server hosts five schedules that each execute once a day: Weekday 3:00 PM Extract Refresh, Weekday 5:00 PM Subscription, Weekday 2:00 AM Extract Refresh, Weekday 7:00 AM Extract Refresh, and Weekday 8:00 AM Subscription. The schedules are scheduled to execute during periods when Tableau Server is least active. The busiest period for your server is immediately after the workday begins at 9:00 AM. The office of the CEO reports that every morning at 9:00 AM, they access the views in a particular workbook. The data for these views is refreshed by a task associated with the 7:00 AM schedule. The CEO reports that the data in the views is only being refreshed about
70% of the time. What should you do to attempt to resolve the CEO's problem?
Answer: C
Explanation:
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.
NEW QUESTION # 71
You have an existing group subscription. You add a user to the group. What statement correctly describes the result?
Answer: B
Explanation:
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 via Workbooks > 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., via Users > 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.
NEW QUESTION # 72
Which two statements are advantages of published data sources in comparison to embedded data sources? (Choose two.)
Answer: A,C
Explanation:
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.
NEW QUESTION # 73
What is the minimum hardware recommendation for a single-node production installation of Tableau Server?
Answer: A
Explanation:
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.
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).
NEW QUESTION # 74
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