Explanation
You don't need to know ANY programming language to use quick table calculations!
Follow along with the steps below to learn how to apply a quick table calculation to a visualization:
1) Open Tableau Desktop and connect to the Sample-Superstore data source, which comes with Tableau.
2) Navigate to a new worksheet.
3) From the Data pane, under Dimensions, drag Order Date to the Columns shelf.
4) From the Data pane, under Dimensions, drag State to the Rows shelf.
5) From the Data pane, under Measures, drag Sales to Text on the Marks Card.
6) From the Data pane, under Measures, drag Profit to Color on the Marks Card.
7) On the Marks card, click the Mark Type drop-down and select Square.

The visualization updates to look like this:

Apply the quick table calculation
1) On the Marks card, right-click SUM(Profit) and select Quick Table Calculation > Moving Average.
Note: You can only perform quick table calculations on measures in the view.
A delta symbol appears on the field to indicate that a quick table calculation is being applied to the field. The colors in the visualization update to show the moving average of profit across the years.

When using a Blend, the primary data source appears with a BLUE tick-mark and the secondary data source appears with a ORANGE tick-mark.
See below:

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.

By default, the shape that a Heap map uses is a "Square". See below:

Explanation
For relational data sources, dates and times are automatically placed in the Dimensions area of the Data pane and are identified by the date or date-time icon. For example, the Order Date and Ship Date dimensions from an Excel data source are shown below:

When you place a relational date on a shelf, the field name is automatically modified to reflect the default date level. Tableau defines the default date level to be the level at which there are multiple instances. For example, if the date field includes multiple years, the default level is year. However, if the date field contains data for just one year but includes multiple months, then the default level is month.