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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Exploring and Analyzing Data | 37% | - Apply calculations and aggregations - Use filters, parameters, and sets - Sort, group, and summarize data - Create and customize visualizations - Create interactive dashboards and stories |
| Topic 2: Connecting to and Preparing Data | 23% | - Manage data fields and hierarchies - Connect to various data sources - Join and union data - Data cleaning and transformation |
| Topic 3: Sharing Insights | 25% | - Set permissions and access - Export and publish visualizations - Ensure accessibility and clarity - Publish and share workbooks |
| Topic 4: Understanding Tableau Concepts | 15% | - Dimensions vs measures - Visualization best practices - Data types and roles - Workbook, worksheet, and dashboard structure |
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NEW QUESTION # 36
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: B
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 # 37
Which aggregation is available without requiring a table calculation or calculated field?
Answer: A
Explanation:
Standard deviation is available as a native aggregation for a measure and does not require the author to create either a table calculation or a calculated field. Therefore, C is correct. When a measure is used in a Tableau view, its aggregation can be changed through the field menu. In addition to commonly used functions such as SUM, AVG, MIN, MAX, and COUNT, Tableau provides Standard Deviation and Standard Deviation (Population) as built-in aggregation choices. The calculation is performed directly over the records contributing to the current mark. Running Total and Percent of Total are different because they are table calculations. They operate on already aggregated values after Tableau has constructed the visualization and depend on the addressing and partitioning of the view. Sample covariance is supported through calculation functionality such as covariance functions but is not presented as the equivalent direct aggregation option in the basic measure aggregation menu represented by this question. Implementing covariance typically involves specifying the two expressions whose covariance is required. Tableau's official Data Aggregation documentation explicitly lists standard deviation among the aggregations available for measures, including sample and population forms. Consequently, it can be selected directly without constructing an additional calculated field or applying a quick table calculation.
NEW QUESTION # 38
What is a Tableau story point?
Answer: B
Explanation:
A story point is an individual visualization state within a Tableau story, normally represented by a worksheet or dashboard. Therefore, A is correct. Tableau defines a story as a sequence of visualizations that collectively communicate information, provide context, demonstrate relationships, or support a data-driven narrative.
Each individual sheet contained in that sequence is called a story point. A story can contain multiple points, and each point can present a different worksheet, dashboard, filter state, annotation, or analytical stage.
Option C describes the overall story, not an individual story point. The distinction is important: the story represents the complete ordered narrative, while the story point represents one step within that narrative.
Option B is not an official Tableau object or definition. Option D refers to controls within the story workspace and does not define a story point. This functionality allows an analyst to guide viewers through findings in a controlled sequence while preserving interactive visualization capabilities where supported. Official Tableau Desktop documentation explicitly states that a story is a collection of sheets arranged in sequence and that each individual sheet in a story is called a story point.
NEW QUESTION # 39
A Tableau associate needs to change the color intensity of a quantitative range.
Which option should the associate use?
Answer: D
NEW QUESTION # 40
Which chart type uses automatically generated sizes that cannot be resized by using the Marks card?
Answer: C
Explanation:
The correct answer is Treemaps. A treemap represents data as a set of rectangles. Tableau uses one or more dimensions to define the rectangular structure, while a measure placed on Size determines each rectangle's relative area. Tableau automatically lays out the rectangles to use the available visualization space efficiently.
The analyst therefore controls relative size through the measure encoded on Size rather than manually resizing the generated rectangles with the ordinary Marks card size slider. For example, if Sub-Category defines the rectangles and Sales is placed on Size, categories with larger aggregated Sales values receive proportionally larger rectangles. Changing the Sales values or replacing the field on Size changes the relative areas, while Tableau recalculates the layout automatically. Pie charts have mark-size controls and can be resized through the Marks card. Area charts derive their visual area from their axes and underlying measures. Histograms use bars representing bins and frequencies and have different bar-sizing behavior. Tableau's official Treemap documentation identifies Size and Color as the crucial encodings and explains that a measure on Size determines the areas of the rectangles. The resulting treemap geometry is automatically laid out according to those values rather than manually sized mark by mark.
NEW QUESTION # 41
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