Explanation
According to the official Tableau documentation:

Dimensions don't have aggregation properties, and adding properties manually each time defeats the whole DEFAULT aggregation purpose. Window tab doesn't have any default aggregation option!

Explanation
To interactively display information from the web INSIDE a dashboard, you can use a URL action with a web page object.
For example, you might have a dashboard that shows profits by country. In addition to showing the profit data in your dashboard, you also want to display supplemental information about the countries from a web site.

Explanation
Sets are custom fields that are created within Tableau Desktop based on dimensions from your data source.
They are subsets of your data, which can be created manually or computed. Either dimensions or measures can be used to determine what is included or excluded from a set using conditional logic, but to CREATE a set we use dimensions.


Reference : https://interworks.com/blog/rcurtis/2016/10/26/tableau-deep-dive-sets-introduction-sets/

Explanation
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.

Explanation
You can create aliases (alternate names) for members in a dimension so that their labels appear differently in the view.
Aliases can be created for the members of discrete dimensions only. They cannot be created for continuous dimensions, dates, or measures.
To create an alias:

1) In the Data pane, right-click a dimension and select Aliases.
2) In the Edit Aliases dialog box, under Value (Alias), select a member and enter a new name.

* To submit your changes: In Tableau Desktop, click OK.
On Tableau Server or Tableau Online, click the X icon in the top-right corner of the dialog box.
When you add the field to the view, the alias names appear as labels in the view. For example: