For a relative date filter, the default anchor is _________________
Answer(s): B
Relative date filters dynamically update to show a time period relative to when you open the view, such as the current week, the year to date, or the past 10 days. Relative date filters make it easy to create views that always show the most recent data.Step 1: Drag a date field to the filter shelfRight-click (control-click on Mac) and drag a date field from the Data window to the Filters shelf. In the Filter Field dialog box, click Relative Date, and then click Next.Step 2: Select a time unitIn the Filter dialog box, click Relative dates, and then select the unit of time for the filter. For example, to show only the three most recent weeks, select Weeks.Here, you can clearly see that the default date is TODAY
https://help.tableau.com/current/pro/desktop/en-us/qs_relative_dates.htm
True or False: To concatenate fields, they must be of same data type
Answer(s): A
Yes! To concatenate fields, they must be of same data type. However, there is a workaround which we can use - Type casting. See below:Here, State and City are Strings, but Postal Code? Nope. It's an Integer. So we can simply use the STR() function to convert it into a String, and hence the entire equation becomes valid!
Which of the following are valid ways to trigger actions for a Dashboard?
Answer(s): A,C,D
Whenever we want to add actions to a Dashboard, we can trigger then in the following 3 ways:1) Select2) Hover3) MenuHover is best for highlighting, select for filtering. Menu action is added to the tooltip and user can decide whether to run that action or not (best for URL actions)
https://help.tableau.com/current/pro/desktop/en-us/actions_dashboards.htm
_____________ is a snapshot of the data that Tableau stores locally. Good for very large datasets of which we only need few fields.
Answer(s): C
Tableau Data Extract (TDE) is a snapshot of the data that Tableau stores locally. Good for very large datasets of which we only need few fields. Performance is optimised because it queries its own database engine instead of the local data source.When you create an extract of your data, you can reduce the total amount of data by using filters and configuring other limits. After you create an extract, you can refresh it with data from the original data. When refreshing the data, you have the option to either do a full refresh, which replaces all of the contents in the extract, or you can do an incremental refresh, which only adds rows that are new since the previous refresh.Extracts are advantageous for several reasons:1) Supports large data sets: You can create extracts that contain billions of rows of data.2) Fast to create: If you're working with large data sets, creating and working with extracts can be faster than working with the original data.3) Help improve performance: When you interact with views that use extract data sources, you generally experience better performance than when interacting with views based on connections to the original data.4) Support additional functionality: Extracts allow you to take advantage of Tableau functionality that's not available or supported by the original data, such as the ability to compute Count Distinct.5) Provide offline access to your data: Extracts allow you to save and work with the data locally when the original data is not available. For example, when you are traveling.
We can use ______________ as a static tool to open and interact with packaged workbooks with extracted data sources that have been created in Tableau Desktop.
The word 'static tool' gives it away.According to the official website :
https://help.tableau.com/current/reader/desktop/en-us/reader_welcome.htm
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please provide dumps
is the answer to question 15 correct ? i feel like the answer should be b
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answer to 134 is casb. while data loss prevention is the goal, in order to implement dlp in cloud applications you need to deploy a casb.
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