Tableau Desktop-Specialist Exam With Confidence Using Practice Dumps

Explanation

If you chose 2, then you were very close but probably didn't plot the actual Percent Difference on your view. ( One of the marks is just over the line).

• Firstly, Drop the Week ID onto the column shelf, and convert it to continuous since we need both Year and Quarter as mentioned in the question.
• 2) Next, Drop assortment to filters shelf so that we can focus on Electronics!

3) This should be your view now. Click on the Show Mark Labels icon as shown:

The final view is as follows, with 3 points below 0 ( i.e negative )

Explanation

If you answered this question quickly and correctly, you're well prepared for the exam! Most students stumble while creating a Dual axis chart, so go ahead and give yourself a pat on the back!

To create a dual axis chart for the problem mentioned:

1) Drag Product Type to the column shelf, and Sales and Profit to the Row shelf:

2) Now, to focus on 2013, drag Date to the filter shelf and select only 2013:

3) Now, click on the Profit pill in the Rows Shelf, and select dual axis:

4) Now, in the marks shelf, choose Sales, and change the chart type to bar. Similarly, for Profit, change the chart type to Line.

Now the chart looks like this:

Now we change the Profit chart type to line:

5) Finally, we synchronise the axis as follows: Right click on the axis, and choose 'Synchronise axis'

And, our final view and answer is:

In fact, the opposite of this is true.

Trick : Whenever you think of joins -> Think that after the join is created, we get 1 single flat combined (joined) table. This flat combined table is created prior to us creating our visualizations. This happens at the physical layer.

If you ever think about relationships, know that all tables will remain distinct and separate, and relationships sit at the logical layer. At run time, when you bring in the dimensions and measures to create your viz, Tableau very smartly creates the necessary joins, relates the tables and sends queries to these tables to get the resultant data back in the most meaningful way possible. This allows you to focus on using your data and revealing insights from it and focus less on the data preparation aspect!

Refer to logical layer vs physical layer from the official documentation: