MIS 3360 Spring 2019 Assignment #5
Assignment #5 pertains specifically to Section 5 of the Udemy course Tableau 10 A-Z:
Hands-On Tableau Training for Data Science. I want you to fully explain and answer
the following questions in written form. Please base your answers on the content in
Section 5: Joining and Blending Data, PLUS: Dual Axis Charts. Please email me your
completed exercise not later than Monday, April 29th, by 4PM. As always, include your
name, MIS 3360, and assignment5 in the Word or pdf file that you send me, for example:
geoffrey_hubona_MIS3360_assignment5.pdf. You can actually use this word file as your
template for completing this exercise by simply typing in your written answer to each
question directly underneath each question. In your answers, please address each part
of each question that is asked. You will lose points if you do not pay attention to the entire
question and address each aspect and detail asked.
1) Joins are operations that are performed on tables in relational databases. How does
an inner join work? What rows remain in the table resulting from the inner join? Use
Kirill’s example to illustrate. Try to explain the process in a little detail.
-An inner join compares attributes from a two sets of data and if the data appears in both
sets it will only get the entire row of data that are common between the sets of data.
2) How about a left join (also called a left outer join sometimes)? Which rows are
discarded from which table? Continue to use Kirill’s example to illustrate the outcome.
-A left join will contain all of the rows from the left table and will only keep the rows with
the common attribute from the right table. The rows not containing the common attribute
will be discarded.
3) How about a right join (also called a right outer join sometimes)? Which rows are
discarded from which table? Continue to use Kirill’s example to illustrate the outcome.
-A right join will contain all of the rows from the right table and will only keep the rows with
the common attribute from the left table. The rows not containing the common attribute
will be discarded.
4) How about a full outer join? Which rows do we consider to include in a full outer join
of the two tables? Which rows do we discard? Continue to use Kirill’s example to illustrate
the outcome.
-A full outer join will contain all of the rows from the right table and left table. No rows
discarded.
5) What happens when the single column we are joining on has duplicate values in one
of the tables? Describe what happens, how you must proceed in this situation.
-When a single column in a table has duplicate values in one of the tables it will duplicate
the data of the side that is not duplicated when joined.
6) Blending is a very smart join that we can create on the fly. Kirill specifically calls out
two separate reasons why you might want to perform a blend instead of a join at the end
of video 31 The Showdown: Joining Data vs. Blending Data in Tableau. What are
these two reasons?
-The levels of granularity are different to which it would lose data if created a join instead
of a blend. An the second reason is when the data sources are different.
7) What is a dual axis chart? Kirill provides a long-winded example in video 33 Dual
Axis Chart but I just want you to describe, conceptually, what a dual axis chart is. That
is, why do you think it is called a dual axis chart? What are the two “point and click” steps
in Tableau that he shows you to follow when creating a dual axis chart (you may use his
example)?
-A dual axis chart combines the charts. Like if you have two charts and want to compare
them one over the other. It is called dual axis because you can place both the x axis and
the y axis of both charts to be in one chart. The two steps are, right click on the left target
and choose dual axis. Then right click on the target of the right and click synchronize axis.