Explanation
When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains. You use these fields to build views of your data.
Further,

Explanation
According to the official Tableau documentation:
Tableau packaged workbooks have the .twbx file extension. A packaged workbook is a single zip file that contains a workbook along with any supporting local file data and background images. This format is the best way to package your work for sharing with others who don't have access to the original data. For more information, see Packaged Workbooks.

Explanation
When users connect to Tableau, the data fields in their data set are automatically assigned a role and a type.
Role can be of the following two types:
1) Dimension
2) Measure
Type can be of the following :
1) String
2) Number
3) Geographic
4) Boolean
5) Date
6) Date and Time

Explanation
As the question mentions, we need to create a SET with the following conditions -> Choose only those customers whose Sales > 30,000
1) Right click on customer name --> Create --> Set

2) Let's Name the Set - Customer>30k ( you can name it anything you want :) ) Select USE ALL, and then move to the CONDITION TAB:

3) In the Condition Tab, Choose BY FIELD -> Select Sales -> Sum -> Greater than 30000 , and click OK

4) You should now have a new Set in the Data Pane as follows:

5) Drag this set to the rows shelf, and click on SHOW MEMBERS IN SET. Now drag Sales to the Column Shelf.

6) Click on the Show Mark Labels, and Sort ascending icons as shown:

7) Voila! We have our answer:
c

Explanation
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.
To work with the MOST up-do-date data, use a live connection instead!