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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Connecting to and Preparing Data | 23% | - Manage data properties - Create live connections and extracts - Create and manage the data model |
| Topic 2: Understanding Tableau Concepts | 15% | - Understand discrete and continuous fields - Understand dimensions and measures - Understand aggregations |
| Topic 3: Exploring and Analyzing Data | 37% | - Organize data and apply filters - Apply analytics to a worksheet - Create basic charts |
| Topic 4: Sharing Insights | 25% | - View and share workbook data - Create and modify a dashboard - Format view for presentation |
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NEW QUESTION # 23
Which type of date filter can a Tableau associate use to choose a range of dates based on TODAY()?
Answer: D
Explanation:
A Relative dates filter is designed for date ranges that dynamically change relative to the current date, making B correct. This filter can represent periods such as the current week, previous month, year to date, or the last specified number of days, weeks, months, quarters, or years. The important distinction is that a relative date filter is dynamic. As the current date advances, Tableau recalculates the applicable range when the view is opened or refreshed. This behavior is appropriate for requirements based conceptually on TODAY() because the filter should continue tracking the present period rather than retaining fixed start and end dates. A Range of dates filter establishes a specific date interval and is better suited to fixed boundaries. A Starting Date or Ending Date represents an open-ended boundary from a particular date rather than a dynamically shifting interval relative to today. Tableau's official documentation states that relative date filters dynamically update to display a time period relative to when the view is opened. Examples include the current week, year to date, or past ten days. This functionality allows analysts to create dashboards that consistently display the most recent period without manually editing the filter as calendar time progresses. Relevant topics include date fields, relative date filtering, dynamic analysis, and interactive filter configuration.
NEW QUESTION # 24
A Tableau associate has a continuous numeric measure named Sales.
Which chart type is created when the associate double-clicks the Sales measure?
Answer: C
Explanation:
Double-clicking a continuous numeric measure such as Sales in an empty Tableau worksheet automatically produces a bar chart, making C correct. Tableau uses intelligent defaults when fields are double-clicked in the Data pane. With a single measure and no dimensions already defining the view, Tableau aggregates the measure-normally using its default aggregation such as SUM-and adds it to the visualization. The Automatic mark type resolves to a bar, producing a single bar representing the aggregated Sales value.
Tableau's official documentation provides this exact construction using the Profit measure. It states that double-clicking Profit automatically adds the field to the view in an intelligent way, and the documented resulting visualization is a bar chart of Profit. Sales is the same type of field-a quantitative measure-so the same automatic-view rule applies. A line chart ordinarily requires an ordered dimension such as a date field to provide a sequence across which values can be connected. A pie chart requires additional categorical structure for meaningful segmentation. A text table is generally created when a dimension is double-clicked first and subsequent fields refine that cross-tabular structure. Therefore, a lone continuous numeric measure double- clicked in a new worksheet produces the automatic single-measure bar visualization.
NEW QUESTION # 25
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 # 26
From which three locations can a Tableau associate sort a visualization?
Choose three options.
Answer: B,C,D
Explanation:
Tableau provides direct single-click sorting controls from a header, an axis, and a field label, making A, C, and D correct. Tableau's official Sort Data in a Visualization documentation explicitly identifies these three locations. When the user hovers over an appropriate header, numerical axis, or field label, Tableau can display a sort icon. One click typically applies descending sorting, a second click changes it to ascending, and another interaction can clear the sort depending on context. A header is commonly generated by a discrete field and can expose sorting for its members. A numerical axis allows the associated categorical members to be sorted according to measure values. A field label can similarly provide direct sorting when applicable to the view's structure. The Tooltip area of the Marks card controls information displayed when the pointer hovers over a mark; it is not a sorting interface. The Worksheet and Analysis menus contain numerous authoring commands but are not the three direct locations identified by Tableau's single-click sorting workflow in this question.
Official Tableau documentation specifically states: "Quickly sort from an axis, header, or field label," precisely matching A, C, and D.
NEW QUESTION # 27
What allows a Tableau associate to drill up or down in the level of detail (LOD)?
Answer: C
Explanation:
Hierarchies provide Tableau's native mechanism for drilling up and down through related levels of detail, making A correct. A hierarchy organizes dimensions into an ordered structure such as Region > State > City, Category > Sub-Category > Product, or a standard date hierarchy such as Year > Quarter > Month > Day.
When a hierarchy field is placed in a visualization, Tableau displays plus and minus controls that permit the analyst to expand to a more detailed level or collapse to a higher level. Drilling down adds another hierarchy level to the view, increasing the level of detail. Drilling up removes a lower level and returns the analysis to a more aggregated perspective. This functionality allows analysts to move through different analytical granularities without manually adding and removing each related field. Bins serve a different purpose: they partition continuous numeric values into intervals. Groups consolidate selected dimension members into broader categories. Sets identify subsets of data according to membership logic or user selections. None of those constructs inherently provides structured drill-up/drill-down navigation. Tableau's official hierarchy documentation explicitly states that hierarchies allow users to quickly drill up or down to add or subtract levels of detail and identifies the plus and minus icons as the controls used for this operation.
NEW QUESTION # 28
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