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| Section | Objectives |
|---|---|
| Connecting to Data | - Data preparation basics
|
| Understanding Tableau Concepts | - Core Tableau terminology
|
| Sharing Insights | - Publishing and sharing
|
| Exploring and Analyzing Data | - Basic calculations
|
>> Analytics-101 Actual Questions <<
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NEW QUESTION # 40
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 # 41
What are two correct methods for creating a visual group?
Answer: B,C
Explanation:
Tableau supports creating groups either directly from selected marks in a visualization or from a field in the Data pane. Therefore, A and D are correct. For the first method, the analyst selects one or more marks in the view. Tableau exposes a grouping control in the selection tooltip or toolbar. Activating the Group command combines the dimension members represented by those marks into a new group. This method is particularly effective when the analyst identifies categories visually during exploration. For the second method, the analyst can right-click a dimension in the Data pane and select Create > Group. Tableau opens the Create Group dialog, where multiple members can be selected and grouped explicitly. Option C represents another Tableau capability, but not grouping: dragging one dimension directly onto another in the Data pane is used to create a hierarchy. Hierarchies organize related dimensions into drillable levels rather than consolidating dimension members into a group. Opening the general drop-down menu at the top of the Data pane is likewise not the specified procedure for creating a visual group. Tableau's official Group Your Data documentation identifies exactly these two core workflows: create a group by selecting data in the view or create a group from a field in the Data pane.
NEW QUESTION # 42
A Tableau associate is creating a combined axis chart.
Where should the associate drag the second measure after dragging the first measure to the Rows shelf?
Answer: C
Explanation:
Because the first measure is on the Rows shelf, Tableau creates a vertical quantitative axis in the visualization. To construct a combined axis, the associate should drag the second measure directly onto that existing vertical axis, making B correct. A combined axis allows multiple measures to share the same axis instead of displaying them in separate panes or on independent dual axes. When the second measure is dragged onto the existing axis and Tableau displays the appropriate drop indicator, Tableau creates a shared Measure Values-based view containing both measures. The orientation matters. Fields on Rows normally produce a vertical y-axis, whereas fields on Columns normally generate a horizontal x-axis. Consequently, because the first measure was specifically placed on Rows, the target is the vertical axis rather than the horizontal axis. Dropping the second measure on the Marks card would encode that field through a mark property rather than create a combined quantitative axis. Dropping it on Filters would restrict records or values and would not combine the measures. This mechanism should also be distinguished from a dual-axis chart, where two independent axes are layered. A combined axis instead places multiple measures on a shared axis and commonly uses Measure Names and Measure Values for differentiation.
NEW QUESTION # 43
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 # 44
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 # 45
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