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Salesforce Analytics-101 Exam Syllabus Topics:

SectionWeightObjectives
Understanding Tableau Concepts15%- Understand dimensions and measures
- Understand aggregations
- Understand discrete and continuous fields
Connecting to and Preparing Data23%- Manage data properties
- Create and manage the data model
- Create live connections and extracts
Sharing Insights25%- View and share workbook data
- Format view for presentation
- Create and modify a dashboard
Exploring and Analyzing Data37%- Apply analytics to a worksheet
- Organize data and apply filters
- Create basic charts

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Salesforce Certified Tableau Desktop Foundations Sample Questions (Q32-Q37):

NEW QUESTION # 32
Which two types of fields appear blue?

Answer: C,D

Explanation:
In Tableau, blue identifies discrete fields, regardless of whether the field is classified as a dimension or a measure. Therefore, both Discrete dimensions and Discrete measures appear blue, making B and C correct.
Tableau separates two different field characteristics. The first is the semantic role: dimension or measure. The second is the behavioral classification: discrete or continuous. These concepts are related but not equivalent.
A discrete field contains distinct values and normally creates headers when added to Rows or Columns.
Tableau represents the pill in blue. Most dimensions are discrete by default, so blue dimensions are common.
Measures are generally continuous, but a measure can be converted to discrete; once it is discrete, its pill also becomes blue. Continuous fields appear green. Continuous dimensions-most commonly continuous date dimensions-and continuous measures therefore use green pills and typically create axes rather than headers.
Tableau's official Dimensions and Measures documentation explicitly presents four valid combinations:
discrete dimensions, continuous dimensions, discrete measures, and continuous measures. It shows discrete dimensions and discrete measures as blue, while both continuous forms are green. This distinction is foundational to predicting how Tableau will structure a visualization.


NEW QUESTION # 33
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: A

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 # 34
A Tableau associate needs to share a workbook with a user who does NOT have access to the underlying data.
The user must be able to modify existing visualizations.
What should the associate do?

Answer: C

Explanation:
The associate should save the workbook as a Tableau Packaged Workbook (.twbx). A packaged workbook can contain the workbook itself together with copies of supported local data sources, Tableau extracts, background images, and other workbook resources. This directly addresses the scenario because the recipient does not have access to the original underlying data. When appropriate data is packaged with the workbook, the recipient can open the workbook in Tableau Desktop and interact with or modify its existing worksheets and visualizations without requiring the author's original file paths. A .twb file contains the workbook definition but normally references external data rather than packaging the required local resources. Therefore, it would not reliably solve the access problem. Creating a .hyper file alone provides an extract but does not contain the complete Tableau workbook, including worksheets, dashboards, calculations, formatting, parameters, and visualization definitions. Exporting views produces presentation-oriented outputs and does not satisfy the requirement to modify the existing Tableau visualizations. Tableau specifically recommends packaged workbooks when sharing with someone who does not have access to referenced resources or the original environment.


NEW QUESTION # 35
What are two correct methods for creating a visual group?

Answer: A,D

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 # 36
Which two actions can a Tableau associate perform when joining tables from multiple connections?

Answer: A,C

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 # 37
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