Uncategorized

ISM3011 University of South Florida Books and Publishers Worksheet https://onlinehelp.tableau.com/current/guides/get-started-tutorial/en-us/get-started-tut

ISM3011 University of South Florida Books and Publishers Worksheet https://onlinehelp.tableau.com/current/guides/get-started-tutorial/en-us/get-started-tutorial-build.htmUsing the files and the link provided, create a dashboard using the instructions provided from the files and links. The link does give specific steps to be done. Tableau 2 – Project from a Past Semester
Part 1) The Data – A paragraph describing the data – what’s included in the columns and rows and how you
approached the analysis of this data. This should include: 1) what you did to initially analyze the data, 2) how the
initial data analysis influenced the types of visualizations you included, 3) any problems you had and 4) any changes in
your thoughts about the data as you worked through the project.
The data basically went over several different products and details of its progression through the course of 4
years. It encompassed self-hygiene products throughout the United States and its affiliated regions, and
provided the sales, profits; and the profit ration in-between. When I looked through it, I analyzed what products
were being sold first, then what the sales and profits came out to be. I picked this first because it seemed to be
the focal point to the rest of the additional details, or rather the most important. Ideally, one thing leads to
another and I used this as the foundation to what would be my visualizations. As I went through deciding on
what visualizations to make, I found it difficult to begin with something substantial without out giving to much
info on the first couple of visualizations. I wanted to explain what the worst selling product was; but, explaining
it in a sequential order that made sense, was quite difficult. What changed was the order of how I presented it,
where I showed the highs and lows of the sales/profits, the locations, and just overall the sales and profits in
tandem. By doing this, it became a lot more cohesive.
Worksheet #1
Part 2) Workbook Sheets – Screenshots of the (at least) 4 sheets that you’ve created. Do not use cell phone pictures.
Below each screenshot, include a detailed paragraph (more than a few sentences) describing: 1) what you are
showing, 2) what led to this visualization and 3) the relevance / importance in relationship to the data. Also include 4)
why you chose the particular visualization format and 5) a response to the question, “Why is this analytic /
visualization meaningful?”
In this screenshot, I am presenting the location of all the sales and profits of each product. The circle’s sizes
represent the amount of sales, and the color scale between red to green shows the profits of each; if it is in the
red, they lost profit and vice versa. After my analysis, I thought this was a good start to show generally where all
the sale’s popularity stood based its designated regions. The importance stands for its most marketable regions
for personal hygiene AND how well it did. I chose the map because it represents the areas better than a chart.
This visualization is meaningful for it the ability to represent geographic locations more tangibly, gaining a better
overarching area of it success or failure, as it is much simpler to digest without having to go through several
spreadsheets.
Worksheet #2
Part 2) Workbook Sheets – Screenshots of the (at least) 4 sheets that you’ve created. Do not use cell phone pictures.
Below each screenshot, include a detailed paragraph (more than a few sentences) describing: 1) what you are
showing, 2) what led to this visualization and 3) the relevance / importance in relationship to the data. Also include 4)
why you chose the particular visualization format and 5) a response to the question, “Why is this analytic /
visualization meaningful?”
With this screenshot, I am representing the areas in which the sales and profits were the lowest; by extension,
which products went below a zero profit. I used this visualization to give a better understanding of the first
screenshot, to narrow WHERE there is fault in the products. This is probably the most important visualization, as
it represents where there is error in the product’s profit, despite the large amount of sales. My reasoning for
using this worksheet is the same reasoning as the previous, it represents the geographical areas of which
products are now fully failing, and there are some differences between the two. This visualization is meaningful
for it the ability to represent geographic locations more tangibly in conjunction with the first map, gaining a
better overarching area of failure to be profitable.
Worksheet #3
Part 2) Workbook Sheets – Screenshots of the (at least) 4 sheets that you’ve created. Do not use cell phone pictures.
Below each screenshot, include a detailed paragraph (more than a few sentences) describing: 1) what you are
showing, 2) what led to this visualization and 3) the relevance / importance in relationship to the data. Also include 4)
why you chose the particular visualization format and 5) a response to the question, “Why is this analytic /
visualization meaningful?”
This worksheet shows the specific product’s sales/profits. Now that it has been established what areas were
failing, now we need to narrow our search to find what specific products aren’t doing too well, and cross
reference to the geographic locations. The importance of this relationship is to find which product was doing the
worst, so we can understand why and where it’s failing. I chose the line graphs, as I felt it was the best way to
represent the apexes and troughs of each product over time. This visualization is meaningful due to its ability to
represent specific times where each product was at its best and worst, allowing us to gain a better understand
to the consumer’s purchasing trends.
Worksheet #4
Part 2) Workbook Sheets – Screenshots of the (at least) 4 sheets that you’ve created. Do not use cell phone pictures.
Below each screenshot, include a detailed paragraph (more than a few sentences) describing: 1) what you are
showing, 2) what led to this visualization and 3) the relevance / importance in relationship to the data. Also include 4)
why you chose the particular visualization format and 5) a response to the question, “Why is this analytic /
visualization meaningful?”
With the final screenshot here, this is a small portion of what Dove’s sales/profits were when at their best and
worst throughout the U.S. After going through the other worksheets, I found that Dove’s body wash had the
worst profit overall comparably to the rest, so I decided to represent where it was doing well and where it was
not (similarly to the first worksheet). The importance of this piece is meant to demonstrate where their was
fault in a more narrowed demonstration. A bar graph was the best option here, as I am not representing over
time; moreover, the highest and lowest sales/profits. This worksheet is most meaningful is understanding which
areas could be potentially looked over in consideration of Dove’s marketing or selling plan overall.
Dashboard
Part 3) Workbook Dashboard – Include a screenshot (not a cell phone picture) of at least 1 dashboard and below the
dashboard a detailed paragraph describing: 1) what the components you included, 2) why you included them and 3)
what’s the point of this collection of sheets – why did you include them together, what’s do they show as a group?
In my dashboard, I decided to present Dove’s Sales and Profits over specific cities, accompanied by a
geographical representation to allow for better visualization of which areas sold and/or profited. Thus, to
furthermore gain a better understanding of the dire situation Dove’s body wash was in, I chose these two
visualizations to convey where the product was mostly undermined, in the hopes of avoiding these areas for
future sales. Ideally, we want to focus primarily on which areas we should look forwards to and focus on the
market that is doing well.
Part 4) The Story – 1) Describe a narrative of how your worksheets and dashboard(s) tell your analysis ‘story’. 2)
Include the points you are making by including them in the ‘story’ and 3) your specific recommendations going
forward.
In summary, my story begins with the general product’s sales and profits all over the United States, so the
audience can gain a good understanding as to which areas are purchasing/profiting the most, while also finding
which products are profiting the least. The next worksheet follows the same geographical representation of the
U.S. of all products sold, but now representing which areas are under performing below breaking-even. We can
see where the areas of the total amount of many products are being sold versus the profit made, so that we as
the audience know how many products are being shipped to these cities. The following worksheet is meant to
continue digging deeper into the underlying problem, and the best way to go about doing this is finding the
source of problem. I found that Dove’s Body wash was the biggest proponent for the loss of profit, despite it’s
reasonable sales. With the last portion of the story, we find the sales and profits of Dove’s Body Wash. Now we
can narrow the underlying issue, where certain cities are failing to profit, and those of which that are. I think the
best way to combat this is to sell a lot less in the areas of the lowest profit and start selling more in the areas
that are. From my understanding, there are many areas that are selling a lot of the body wash, but aren’t
profiting at all, so by removing the surplus; then perhaps, they will break even. But at the end of the day, you
want to profit from your products, so maybe removing the product in general or rebranding it with better
marketing/advertising, more people would be inclined to purchase. No one is going to buy something they don’t
want or don’t care for, so this particular body wash isn’t hitting the market at all comparably to other products.
Part 5) Conclusions – A detailed paragraph describing what you learned about 1) your data and 2) Tableau
So, throughout this project, I think I’ve definitively learned that where you sell your products is extremely
important, because all customers are different, and every city is a different city. I think there are many products
who have interesting trends. There are many areas where certain companies like Dove are trying to push their
product and are clearly failing; especially over a long period of time. A failing investment is worse than no
investment at all. Albeit, there are a lot of products that are doing well, where the obvious big cities like New
York, Los Angeles, San Francisco, etc., are doing quite well due to their large consumer base. It’s also important
to tap into growing markets, or even create new markets in areas that haven’t been reached. It can allow for
products to be the staple product in the area, ideally without any competition. If there is emerging brand trying
to squeeze in, the competition might be hard pressed if said product has become further popular; therefore,
new products attempting to fashion themselves in areas such as these might struggle, due to the invisible
barrier these situations present. It takes a little bit to fiddle with, but Tableau is an ingenious program that
enlivens statistics better than many built in programs like Excel. It’s the PowerPoint of the data visualizations,
making it super easy to digest for anyone looking at the data.
Country
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
Region
Central
East
East
East
East
East
East
East
East
East
East
East
East
East
East
West
West
West
West
West
West
West
West
South
South
South
South
South
South
South
South
South
Central
Central
Central
East
East
East
East
Central
Central
Central
Central
Central
Central
Central
State
Texas
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Texas
Texas
Texas
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Zip Code
79605
44312
44312
44312
44312
44312
44312
44312
44312
44312
44312
44312
44312
44312
44312
87105
87105
87105
87105
87105
87105
87105
87105
22304
22304
22304
22304
22304
22304
22304
22304
22304
75002
75002
75002
18103
18103
18103
16602
79109
79109
79109
79109
79109
79109
79109
City
Abilene
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Akron
Albuquerque
Albuquerque
Albuquerque
Albuquerque
Albuquerque
Albuquerque
Albuquerque
Albuquerque
Alexandria
Alexandria
Alexandria
Alexandria
Alexandria
Alexandria
Alexandria
Alexandria
Alexandria
Allen
Allen
Allen
Allentown
Allentown
Allentown
Altoona
Amarillo
Amarillo
Amarillo
Amarillo
Amarillo
Amarillo
Amarillo
Sales Date
11/8/2017
6/1/2017
10/7/2017
1/22/2017
8/24/2017
8/24/2017
10/7/2017
8/24/2017
4/14/2017
4/6/2018
4/6/2018
2/7/2018
5/31/2018
4/6/2018
2/6/2018
8/18/2018
5/1/2017
8/18/2018
12/5/2017
5/22/2017
8/19/2018
1/20/2017
8/10/2017
12/20/2017
8/15/2017
1/26/2017
12/19/2017
1/26/2017
12/20/2018
12/19/2018
12/19/2018
12/19/2018
10/12/2017
3/7/2018
10/11/2017
12/18/2017
9/3/2018
12/18/2017
8/28/2017
4/9/2018
4/9/2018
9/20/2017
11/26/2017
1/24/2018
9/15/2018
2/6/2018
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
Central
West
West
West
West
West
West
West
West
West
West
West
West
West
West
West
West
West
West
East
East
East
Central
Central
Central
Central
West
South
South
South
South
South
South
West
West
West
West
West
West
Central
South
South
Central
Central
South
South
South
Texas
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
Massachusetts
Massachusetts
Massachusetts
Michigan
Michigan
Michigan
Michigan
California
Florida
Florida
Florida
Florida
Florida
Florida
California
California
California
California
California
California
Wisconsin
Virginia
Virginia
Texas
Texas
Virginia
Virginia
Virginia
79109
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
92804
1810
1810
1810
48104
48104
48104
48104
94509
32712
32712
32712
32712
32712
32712
92307
92307
92307
92307
92307
92307
54915
22204
22204
76017
76017
22204
22204
22204
Amarillo
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Anaheim
Andover
Andover
Andover
Ann Arbor
Ann Arbor
Ann Arbor
Ann Arbor
Antioch
Apopka
Apopka
Apopka
Apopka
Apopka
Apopka
Apple Valley
Apple Valley
Apple Valley
Apple Valley
Apple Valley
Apple Valley
Appleton
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
5/8/2018
12/7/2017
1/13/2018
1/14/2018
1/11/2018
4/24/2018
6/20/2017
1/14/2018
4/25/2018
1/14/2018
4/25/2018
1/14/2018
4/25/2018
4/25/2018
8/11/2018
4/25/2018
5/19/2018
4/25/2018
4/25/2018
4/22/2018
4/22/2017
4/22/2018
3/18/2018
2/5/2018
2/5/2017
2/4/2018
4/20/2018
5/15/2018
5/15/2018
3/14/2017
3/10/2018
3/10/2018
3/14/2017
2/14/2017
2/14/2017
4/30/2018
4/6/2017
2/14/2017
4/7/2017
2/2/2017
1/31/2018
4/13/2018
4/11/2017
8/16/2017
1/30/2017
6/26/2018
1/31/2018
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
South
South
South
South
South
Central
Central
South
South
Central
Central
Central
Central
South
South
South
Central
Central
South
South
Central
Central
Central
Central
South
South
Central
Central
South
South
South
Central
Central
Central
South
West
West
West
West
South
South
South
South
South
South
South
South
Virginia
Virginia
Virginia
Virginia
Virginia
Texas
Texas
Virginia
Virginia
Texas
Texas
Texas
Texas
Virginia
Virginia
Virginia
Texas
Texas
Virginia
Virginia
Texas
Texas
Texas
Texas
Virginia
Virginia
Texas
Texas
Virginia
Virginia
Virginia
Texas
Texas
Texas
Virginia
Colorado
Colorado
Colorado
Colorado
North Carolina
North Carolina
North Carolina
Georgia
Georgia
Georgia
Georgia
Georgia
22204
22204
22204
22204
22204
76017
76017
22204
22204
76017
76017
76017
76017
22204
22204
22204
76017
76017
22204
22204
76017
76017
76017
76017
22204
22204
76017
76017
22204
22204
22204
76017
76017
76017
22204
80004
80004
80004
80004
28806
28806
28806
30605
30605
30605
30605
30605
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arlington
Arvada
Arvada
Arvada
Arvada
Asheville
Asheville
Asheville
Athens
Athens
Athens
Athens
Athens
1/19/2018
1/30/2017
4/13/2018
3/20/2018
1/24/2018
6/10/2017
4/11/2017
11/9/2017
2/10/2018
5/8/2017
6/13/2017
12/20/2017
12/22/2017
4/1/2018
4/13/2018
5/16/2018
5/1/2018
4/11/2017
9/8/2017
1/24/2018
6/9/2017
6/13/2017
4/11/2017
6/12/2017
11/8/2017
11/9/2017
6/11/2017
4/11/2017
2/2/2017
2/2/2017
11/8/2017
9/15/2018
6/11/2017
6/12/2017
5/23/2018
12/17/2017
12/11/2018
12/16/2017
12/16/2017
9/30/2017
5/17/2018
9/20/2017
10/27/2017
5/18/2018
1/25/2017
9/4/2017
1/24/2017
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
South
East
West
East
South
East
South
East
East
South
East
East
East
South
West
West
Central
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
G…
Purchase answer to see full
attachment

Leave a Reply

Your email address will not be published. Required fields are marked *