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NEW QUESTION # 154
You have a data source that contains data tor every city in the Unites States. The following is a sample of the data.
You need to use the City dimension to create a dynamic filter that snows the cities that have a population greater than one million Which type of filter should you use?
Answer: B
Explanation:
To use the City dimension to create a dynamic filter that shows the cities that have a population greater than one million, you should use a condition filter. A condition filter is a type of filter that shows only the values that meet a specified condition based on a measure or a calculation. You can create a condition filter by dragging a dimension to the Filters shelf and selecting Condition from the dialog box. Then you can enter a formula or choose an option that defines your condition.
In this case, you want to create a condition filter based on Population, which is a measure. You can drag City to the Filters shelf and select Condition from the dialog box. Then you can choose By field from the tab and select Population > Sum > Greater than > 1000000 from the drop-down lists. This will create a condition filter that shows only the cities that have a sum of population greater than one million.
The other options are not correct for this scenario. A general filter is not a specific type of filter, but a term that refers to any type of filter in Tableau. A wildcard filter is a type of filter that shows only the values that match a specified pattern or string, such as "New*" or "*ton". A top filter is a type of filter that shows only the top or bottom N values of a measure or dimension based on a ranking or an aggregation. References:
https://help.tableau.com/current/pro/desktop/en-us/filtering.htm https://help.tableau.com/current/pro/desktop
/en-us/filtering_condition.htm https://help.tableau.com/current/pro/desktop/en-us/filtering_wildcard.htm
https://help.tableau.com/current/pro/desktop/en-us/filtering_topn.htm
NEW QUESTION # 155
A Data Analyst has the following two tables that contain data about the books in a library.
Both tables are incomplete, so there are books missing from the tables.
The analyst needs to use the data from both tables in a single sheet. The solution must ensure that all the data is retained.
How should the analyst connect these tables?
Answer: D
Explanation:
A full outer join preserves every row from both physical tables, returning matched records where possible and null values where a corresponding row does not exist. That directly satisfies the requirement to retain books that appear in only one of the two incomplete tables. A Tableau relationship can also satisfy the requirement because relationships keep logical tables separate and defer physical joining until analysis time.
Tableau dynamically determines the appropriate joins based on fields used in the visualization and makes the row and column data from related tables potentially available without permanently collapsing the tables. Left or right joins would discard unmatched rows from one side, while an inner join retains only matches.
Therefore, Full outer join or Relationship model is the correct combination.
NEW QUESTION # 156
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: C,D
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 # 157
A Data Analyst has a dataset that contains people and the awards they have won.
Which formula should the analyst use to get the number of people who won an award?
Answer: C
Explanation:
The same person can appear multiple times because an individual may have won several awards.
Consequently, COUNT([Name]) would count award records rather than distinct people and would overstate the number of award recipients. COUNTD([Name] ) returns the number of distinct non-null names, so each person is counted only once regardless of how many award rows are associated with that person. Tableau's aggregate-function documentation defines COUNTD as returning the number of distinct items in a group and demonstrates its use when unique entities must be counted. MAX([Name]) returns a single maximum string value according to the applicable sort sequence. ATTR tests whether a group contains one unique value, while COVAR is a statistical covariance function requiring quantitative expressions. Therefore, C correctly counts unique award-winning people.
NEW QUESTION # 158
A Data Analyst has a data source that contains data for every city in the United States. The following is a sample of the data.
The analyst needs to use the City dimension to create a dynamic filter that shows the cities that have a population greater than 1 million.
Which type of filter should the analyst use?
Answer: A
NEW QUESTION # 159
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