After creating a dual axis chart, make sure to synchronise their axis since they both might not be having the same y-axis.

To align the two axes in a dual axes chart to use the same scale, right-click (control-click on Mac) the secondary axis, and select Synchronize Axis. This aligns the scale of the secondary axis to the scale of the primary axis.
In this example, the Sales axis is the secondary axis and the Profit axis is the primary axis.
If you would like to change which axis is the primary, and which axis is the secondary, select the field on the Columns or Rows shelf that is the secondary, and drag it in front of the primary field on the shelf until you see an orange triangle appear.
In this example, you can select the SUM(Sales) field on the Rows shelf, and drag it in front of the SUM(Profit) field. The Sales axis is now the primary and the Profit axis is the secondary.

Explanation
According to Tableau's order of operations, the Extract filter is right at the top of the hierarchy. The data filtered in the Extract is then passed on to what we see in the Data Pane. See below:

Explanation
When you connect to a data source, Tableau automatically separates date fields into hierarchies so you can easily break down the viz. You can also create your own custom hierarchies. For example, if you have a set of fields named Region, State, and County, you can create a hierarchy from these fields so that you can quickly drill down between levels in the viz.

The different aggregations available for a measure determine how the individual values are collected: they can be added (SUM), averaged (AVG), or set to the maximum (MAX) or minimum (MIN) value from the individual row values.
For a complete list of the available aggregations, check out - List of Predefined Aggregations in Tableau.
The level of detail is determined by the dimensions in your view-for information about the concept of level of detail, see How dimensions affect the level of detail in the view.
Disaggregating your data can be useful for analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.
Disaggregating data can be useful when you are viewing data as a scatter plot. See Example: Scatter Plots, Aggregation, and Granularity.

VERY IMPORTANT QUESTION FOR THE EXAM, PAY ATTENTION
1) To find the number of days between order date and shipping date, we will make use of a calculated field:

In the data pane, click on the dropdown arrow, and choose create calculated field.
Let's name this calculated field "ShippingDelay" (you can name it anything you want :) )
2) Use the DATEDIFF() function, and pass it the arguments as follows:

'day' depicts that we want to calculate the number of DAYS between the two dates. The first argument is 'start_date' which is the ORDER_DATE (day the order was placed), the second argument is 'end_date', which is the SHIP_DATE (date the order was shipped). So by subtracting as follows: SHIP_DATE - ORDER_DATE, we can find the delay in shipping.
Click OK.
3) You should now have a new measure as follows:

4) Phew! The hard part is done! Now let's filter by Market to include only LATAM:

5) Drag Country to the view, and the new calculated field 'ShippingDelay' to SIZE on the Marks Shelf as follows:
*You can also click on Show Text Labels to be sure that you're choosing the Largest value*

Clearly, Mexico has the highest Shipping Delay!