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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Exploring and Analyzing Data | 37% | - Organize data and apply filters - Create basic charts - Apply analytics to a worksheet |
| Topic 2: Sharing Insights | 25% | - Create and modify a dashboard - Format view for presentation - View and share workbook data |
| Topic 3: Connecting to and Preparing Data | 23% | - Create and manage the data model - Create live connections and extracts - Manage data properties |
| Topic 4: Understanding Tableau Concepts | 15% | - Understand aggregations - Understand dimensions and measures - Understand discrete and continuous fields |
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NEW QUESTION # 21
What are three geographic roles that a Tableau associate can assign to a field?
Answer: C,D,E
Explanation:
The supported choices are Country, Airport, and City, making A, B, and D correct. A geographic role tells Tableau how the values in a field should be interpreted geographically. Once Tableau recognizes the role, it can associate those values with built-in geocoding information and generate geographic fields such as Latitude (generated) and Longitude (generated) for map creation. Tableau's supported location data includes countries and regions, cities, states and provinces, postal codes, airport codes, and several other standardized geographic structures. Country and City are therefore standard geographic roles. Tableau also supports worldwide airport codes, enabling fields containing appropriate airport identifiers to be interpreted geographically. A general street Address is not one of the standard built-in geographic roles represented by the answer set. Exact street-address mapping normally requires appropriate coordinate information, spatial data, custom geocoding, or another supported technique. Time zone likewise is not a standard geographic role used by Tableau's built-in geocoding model. The distinction matters because assigning an unsupported semantic category does not automatically give Tableau coordinates. Official Tableau Desktop mapping guidance specifically identifies countries, cities, airport codes, and other supported geographic location categories for map creation.
NEW QUESTION # 22
When using a data source that has relationships, how can a Tableau associate add a join between two or more tables?
Answer: D
Explanation:
To create a join in a data source that already uses relationships, the associate must double-click a logical table in the canvas, making C correct. Tableau's data model has two layers. The top-level logical layer contains logical tables connected by relationships. A join cannot be created directly between these logical tables because joins operate in the underlying physical layer. Double-clicking a logical table opens its physical Join
/Union canvas. From there, the associate can drag or double-click additional physical tables and define the required join clauses and join type. This distinction is fundamental to Tableau's modern data model.
Relationships connect logical tables while keeping them separate and preserving their natural level of detail.
Joins merge physical tables into one logical table using an explicitly defined join configuration. Selecting Add in the Connections pane adds another connection; it does not itself create the join. Dragging a table directly onto the top-level logical canvas generally creates a relationship rather than a physical join. Double-clicking a table in the Tables pane is not the step used to enter the physical layer of an existing logical table. Tableau's official documentation explicitly instructs users to double-click a logical table to open the physical layer where joins and unions can be created.
NEW QUESTION # 23
At a minimum, what does a Tableau associate need to create a simple scatter plot?
Answer: B
Explanation:
A basic scatter plot requires one measure on Columns and another measure on Rows, so D is correct. A scatter plot displays the relationship between two quantitative variables. One measure determines the horizontal position of each mark, while the second measure determines its vertical position. For example, placing SUM(Sales) on Columns and SUM(Profit) on Rows establishes a two-dimensional quantitative coordinate system. A dimension may then be added to Detail, Color, Shape, or another Marks property to create separate marks for entities such as customers, products, or states. However, that additional dimension is not the fundamental axis requirement identified by the question. The minimum structural requirement is two quantitative measures defining the x- and y-axes. A dimension plus a measure normally produces a categorical view such as a bar chart rather than a scatter plot. Two dimensions likewise do not supply the pair of quantitative scales required to analyze numerical correlation or distribution. Tableau's visual construction model distinguishes continuous quantitative measures, which generate axes, from discrete fields, which generally create headers. A scatter plot relies on two quantitative axes and therefore requires measures on both Rows and Columns. This is consistent with Tableau's standard scatter-plot construction methodology and its continuous-field behavior.
NEW QUESTION # 24
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 # 25
A Tableau associate has a bar chart that has a dimension on the Columns shelf and a measure on the Rows shelf.
How can the associate make a stacked bar chart?
Answer: D
Explanation:
To convert the existing bar chart into a stacked bar chart, the associate should drag another dimension to Color on the Marks card. The initial bar chart already contains a dimension on Columns and a measure on Rows. Adding another categorical dimension to Color partitions each bar according to the members of that second dimension. Tableau assigns a separate color to each resulting group and, because automatic stacking is enabled for bar marks by default, those groups are displayed cumulatively within each bar. For example, if Category is on Columns and SUM(Sales) is on Rows, adding Segment to Color divides each Category bar into Consumer, Corporate, and Home Office segments while preserving the bar's total Sales magnitude.
Dragging another dimension to Size changes the visual size encoding rather than creating standard stacked segments. Adding another measure to Rows typically introduces an additional axis or measure structure. A measure placed on Color generally creates a quantitative gradient rather than categorical stacked segments.
Tableau's official Stack Marks documentation describes this exact construction: a dimension on Columns, a measure on Rows, and another dimension used to color-encode the marks.
NEW QUESTION # 26
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