The Salesforce Analytics-101 certification verifies that you have a basic understanding of Salesforce Certified Tableau Desktop Foundations concepts and virtualization. Success in the Analytics-101 exam of the Salesforce Analytics-101 certificate also proves your knowledge of basic troubleshooting concepts and data center technology. When you earn the Analytics-101 Certification you will get reliable exam guide materials.
| Section | Objectives |
|---|---|
| Topic 1: Sharing Insights | - Dashboards
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| Topic 2: Connecting to Data | - Data preparation basics
|
| Topic 3: Understanding Tableau Concepts | - Best practices
|
| Topic 4: Exploring and Analyzing Data | - Building views
|
>> Latest Analytics-101 Exam Answers <<
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NEW QUESTION # 13
Which chart type uses automatically generated sizes that cannot be resized by using the Marks card?
Answer: B
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 # 14
What is a Tableau story point?
Answer: C
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 # 15
What are two correct methods for creating a visual group?
Answer: B,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 # 16
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 # 17
Which string function should a Tableau associate use to find a substring within a column and return a Boolean value?
Answer: A
Explanation:
The correct function is CONTAINS, making D correct. Its syntax is conceptually CONTAINS(string, substring), and it returns a Boolean result indicating whether the specified substring exists anywhere within the source string. For example, CONTAINS([Product Name] , "Office") evaluates to TRUE for records where Product Name contains the sequence "Office" and FALSE where it does not. This makes CONTAINS useful for classification calculations, conditional logic, filtering, validation, and text-based segmentation. The other functions perform different operations. RTRIM removes trailing spaces and returns a string. SPLIT separates a string using a delimiter and returns the requested substring component. ENDSWITH does return a Boolean value, but it tests specifically whether the original string ends with the supplied substring. The requirement is to determine whether a substring occurs somewhere within the column value, so ENDSWITH is too restrictive. Tableau's official String Functions reference explicitly defines CONTAINS(string, substring) as returning TRUE when the supplied string contains the specified substring and identifies its output data type as Boolean. The same documentation distinguishes CONTAINS from STARTSWITH, ENDSWITH, trimming functions, and string parsing functions. Relevant topics include calculated fields, string functions, Boolean calculations, and text manipulation.
NEW QUESTION # 18
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