Of course! As an example, see below:
1) Using the Sample Superstore data, let's plot a bar chart showing the Sales for each Category:

Observe that we have 3 marks - Each bar in a bar chart is called a mark. Similarly, each point in a scatter plot is also a mark , and so on for all charts.
1 row by 3 columns means that clearly on the y-axis (Sales), we have only a single mark - a single continous axis, but 3 different marks (Technology, Furniture and Office supplies ) on the x-axis.
2) Now let's add subcategory to the view as well (another dimension):

Observe that the number of marks has increased - i.e the number of Bars.
Also, notice we now have 1 row and 17 columns. Simply because 1 row = Sales (on the y-axis), and on the x-axis, we have 17 different columns (i.e product sub categories!!)

A geographic role associates each value in a field with a latitude and longitude value.
Assigning a geographic role based on the type of location (such as state versus postcode) helps ensure that your data is plotted correctly on your map view. For example, you can assign the City geographic role to a field that contains a list of city names.
To assign a geographic role to a field:
In the Data pane, click the data type icon next to the field, select Geographic Role, and then select the geographic role you want to assign to the field.

When you assign a geographic role to a field, Tableau adds two fields to the Measures area of the Data pane: Latitude (generated) and Longitude (generated).
These fields contain latitude and longitude values and are assigned the Latitude and Longitude geographic roles. If you double-click each of these fields, Tableau adds them to the Columns and Rows shelves and creates a map view using the Tableau background map.

When creating a group by selecting headers in a Tableau view, the newly created grouped dimension replaces the original dimension field on either the Rows or Columns shelf. This grouping action aggregates the selected headers into a single group, and this new group dimension is automatically placed in the view, replacing the original dimension. This functionality allows for more simplified and customized categorization within the data visualization, enhancing the ability to analyze and interpret data according to specific groupings.

According to the official Tableau documentation:

An example of an area chart is shown below:

From the official documentation:
When you have a view with a large amount of data you might want to explore your data interactively and highlight a specific mark or group of marks while still maintaining the context of where those marks show in your view.
To do this you can turn on the Highlighter for one or more discrete fields that are included in your view and that affect the level of detail Example - Here we just want to focus on Public Affairs college dimension, but don't want to filter out or remove the rest of the data:
Chart, scatter chart Description automatically generated

Note that filtering is not the correct option since that would REMOVE the data that doesn't match the filtering criteria.
Reference : https://help.tableau.com/current/pro/desktop/en-us/actions_highlight_highlighter.htm