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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Create Content | 26% | - Build Dashboards and Stories
|
| Topic 2: Explore and Analyze Data | 41% | - Perform Data Analysis
|
| Topic 3: Publish and Manage Content on Tableau Server and Tableau Cloud | 9% | - Publish and Share Content
|
| Topic 4: Connect to and Transform Data | 24% | - Prepare and Transform Data
|
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NEW QUESTION # 137
When using the INCLUDE Level of Detail (LOD) calculation, where should the dimension referenced by the INCLUDE function be located on the sheet?
Answer: D
Explanation:
An INCLUDE LOD expression is specifically useful when a calculation must incorporate a finer-grained dimension that is not already present in the visualization. INCLUDE adds the specified dimension to the level of detail established by the dimensions currently in the view, calculates the expression at that finer grain, and then allows Tableau to reaggregate the result at the view's level. For example, { INCLUDE [Customer Name]
: SUM([Sales] ) } can calculate sales per customer even when Customer Name itself is absent from the displayed view. If the dimension is already present in the view, INCLUDE generally adds no additional granularity for that field. The dimension does not specifically need to reside on the Marks card, Rows
/Columns shelves, or Filters shelf. Therefore, Not in the View is the correct answer.
NEW QUESTION # 138
A Data Analyst configures the When Workbook Opens option in the allowable values section when creating a parameter.
What is a user of a workbook able to do?
Answer: A
Explanation:
The When Workbook Opens setting creates a dynamic parameter domain based on values obtained from a data source field. When the workbook opens-or when the relevant data source is refreshed-Tableau can update the parameter's allowable list or range from the current data rather than retaining a static list created earlier. Consequently, users can select values that currently exist in the refreshed field domain. Option A describes a static list whose values remain limited to what existed when the parameter was initially created.
Option B describes an unrestricted parameter rather than a dynamic list, while option C describes a manually configured fixed range. Tableau's parameter documentation states that selecting When the workbook opens refreshes a List or Range parameter's domain from its data source.
NEW QUESTION # 139
A Data Analyst has the following primary data source that contairis a dimension named Dorm_Code.
The analyst receives the following secondary data source that contains updated dorm codes.
The analyst needs to bring the updated dorm codes into Tableau and use the codes in existing visualizations.
The new dorm codes must use the existing field name of Dorm_Code.
What should the analyst do?
Answer: C
NEW QUESTION # 140
You want to add a comment to March 2020 as shown in the following visualization.
You have the following sets in a Tableau workbook
* Top N Customers
* Customers of 2020
* Top N Products
* Sellers of 2020
Which two sets can you combine? Choose two
Answer: A,B
Explanation:
To combine two sets, they must have at least one dimension in common. In this case, Customers of 2020 and Top N Customers both have Customer Name as a dimension, so they can be combined using set operations such as union, intersection, or difference. Sellers of 2020 and Top N Products have different dimensions (Seller Name and Product Name), so they cannot be combined. References: https://help.tableau.com/current
/pro/desktop/en-us/sets.htm https://help.tableau.com/current/pro/desktop/en-us/sets_create.htm#combine-sets In Tableau, sets can be combined if they are created from the same dimension. From the options provided,
"Customers of 2020" and "Top N Customers" are likely created from the same dimension (Customers).
Therefore, these two sets can be combined to create a new set that includes or excludes members based on the combined criteria. Combining sets like "Top N Products" with "Customers of 2020" would not be feasible unless they are from the same dimension, which is typically not the case.
NEW QUESTION # 141
You have the following map.
You need the map to appear as shown in the following visualization.
What should you do?
Answer: A
Explanation:
The question presents a scenario where a geographic map visualization in Tableau needs to be transformed from a series of discrete circles representing data points to a density map visualization. The density map shows concentrations of data points with a gradient of color, where denser areas are indicated by a darker color.
Here's the explanation for each option:
A). Change the mark type to Density: This is the correct answer because changing the mark type to 'Density' in Tableau creates a density map, which displays the concentration of data points with a color gradient. This is exactly what is needed to achieve the visual effect shown in the second image, where regions with a higher concentration of data points are represented by darker shades.
B). Drag Location to Size on the Marks card: This option would adjust the size of the marks based on the number of locations, which is not relevant to creating a density map. It would result in varying sizes of circles, not a continuous gradient.
C). Change the mark type to Map: The visualization is already using a map. This option would not change the visualization to the desired density map.
D). Drag Population to Size on the Marks card: This would change the size of the circles based on the population values, making some circles larger and others smaller. This is not how a density map is created, which uses color intensity rather than size to show concentration.
E). Change the opacity to 75%: Changing the opacity would affect the transparency of the marks on the map but would not transform the visualization into a density map.
To achieve the visualization shown in the second image, the mark type must be changed to 'Density,' which will produce a heat map-like effect where the color intensity represents the concentration of data points.
Therefore, the correct answer is A. Change the mark type to Density.
To create a density map from a scatter plot of data points, you would change the mark type to Density. This mark type allows you to visualize the concentration of data points in an area, which can be useful for identifying clusters or patterns in geospatial data.
NEW QUESTION # 142
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