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| Section | Objectives |
|---|---|
| Understanding Tableau Concepts | - Core Tableau terminology
|
| Connecting to Data | - Data sources and connections
|
| Exploring and Analyzing Data | - Basic calculations
|
| Sharing Insights | - Dashboards
|
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NEW QUESTION # 31
What are three options to change the scope of a reference line?
Answer: B,C,E
Explanation:
Tableau provides three principal scope levels for reference lines: Entire Table, Per Pane, and Per Cell.
Therefore, A, B, and D are correct. Scope determines the partition of the visualization over which Tableau calculates and displays the reference line. Entire Table computes one reference value based on all applicable marks in the view. This is appropriate for a global benchmark such as overall average Sales. Per Pane creates a separate reference line for each pane. For example, if a visualization is partitioned by Region, Tableau can calculate an independent average for each regional pane. Per Cell is still more granular and can calculate a separate reference line for each cell defined by the row and column structure of the view. Maximum is not a scope; it is a possible statistical value or computation that can be used to determine the reference-line value.
Similarly, Fill Above concerns formatting or shading behavior associated with analytical reference objects and does not define the calculation scope. Official Tableau documentation explicitly states that the terms Table, Pane, and Cell define the scope for reference lines and related analytical objects. These options control whether the benchmark applies globally or independently to specific partitions of the visualization.
NEW QUESTION # 32
A Tableau associate has the following data.
The associate wants to sort each category's sub-category by ascending sales.
Which sort option should the associate use?
Answer: C
Explanation:
The correct option is Nested because the Sub-category members must be sorted independently within each Category based on Sales. A nested sort evaluates the measure separately inside each pane or parent dimensional grouping. In this example, the Home sub-categories should be sorted according to their Home Sales values, while the Bath sub-categories must be sorted independently according to the Bath Sales values.
For Home, Bulk has Sales of $50 and Accessory has $60, so ascending order is Bulk followed by Accessory.
For Bath, Accessory has $45 and Bulk has $75, so ascending order is Accessory followed by Bulk. This demonstrates why a single global ordering is insufficient: the correct Sub-category order differs between the two Category groups. A non-nested field sort can produce a consistent order based on aggregated values across the view, which would not satisfy the requirement to rank Sub-category independently inside each Category. Manual sorting would require explicit maintenance, while data source order simply follows the ordering supplied by the underlying source. Tableau's official sorting documentation states that nested sorting considers values independently per pane and sorts the values separately within those panes.
NEW QUESTION # 33
Which two actions can a Tableau associate perform when joining tables from multiple connections?
Answer: C,D
Explanation:
A multi-connection data source created for a cross-database join can be filtered and can also be converted to or used with an extract, making A and C correct. Cross-database joins allow Tableau to combine tables originating from different supported connections into one logical data source. Tableau supports these joins with either live connections or in-memory extracts. Consequently, the associate can create an extract of the resulting multi-connection data source. Data source filters can also be used to reduce the records Tableau brings into the analytical environment, subject to connector-specific limitations. The other two choices conflict with documented multi-connection restrictions. Tableau explicitly states that stored procedures are not available for multi-connection data sources, eliminating B. A union appends rows from structurally similar tables. In a multi-connection environment, Tableau Desktop requires tables being unioned to come from the same connection; tables from different databases cannot be unioned directly in Tableau Desktop.
Therefore, D does not meet the scenario involving tables across multiple connections. Tableau's official cross- database documentation explains that a cross-database join requires a multi-connection data source, supports both live and extract-based operation, prohibits stored procedures for such sources, and limits unions to tables within the same connection.
NEW QUESTION # 34
A Tableau associate has a data set that builds a union between two tables. The associate needs to extract the data set.
What should the associate use to extract the data set?
Answer: C
Explanation:
The correct configuration is Logical tables that use a single table extract, making C correct. In Tableau's data model, a union operates in the physical layer. The two unioned physical tables are merged into one resulting logical table. Tableau explicitly describes logical tables as containers that can contain multiple physical tables joined or unioned together. When an extract is stored using Logical Tables, Tableau creates one extract table for each logical table in the data source. Because the scenario contains one logical table composed of the two unioned physical tables, the extract is consequently represented as a single extract table. This is different from using Physical Tables storage. Physical storage retains an extract table for each physical table and is subject to additional eligibility restrictions. Tableau's current terminology replaced the older "Single Table" and
"Multiple Tables" extract terminology with Logical Tables and Physical Tables, respectively. Official Tableau documentation states that physical tables joined or unioned inside a logical table are merged as part of that logical table, and that Logical Tables extract storage creates one extract table per logical table. Therefore, a two-table union forming one logical table corresponds to a logical/single-table extract structure.
NEW QUESTION # 35
What are two outcomes when a Tableau associate drags a continuous date value to the Rows shelf?
Answer: A,B
Explanation:
A continuous date field produces a green pill and generates an axis, making B and C correct. Tableau uses color as an immediate visual cue for discrete versus continuous fields. Green pills represent continuous fields, whereas blue pills represent discrete fields. A date can function in either form. When the analyst chooses a continuous date value such as continuous Month or continuous Year, Tableau represents the field as an unbroken temporal range rather than a finite collection of date-part headers. When this continuous date is placed on the Rows shelf, Tableau generates a continuous axis corresponding to the selected temporal granularity. The axis behaves similarly to other continuous quantitative axes in the sense that values occupy positions along an uninterrupted scale. Option A instead characterizes a discrete date part, such as discrete Month, where Tableau creates categorical headers or labels like January, February, and March. Option D is likewise associated with discrete fields because discrete pills are blue. Tableau's official Continuous Dates documentation states that continuous dates create an axis and that converting a date field to continuous causes the field to turn green. Tableau's general field-role documentation separately confirms that continuous fields create axes while discrete fields create headers.
NEW QUESTION # 36
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