About

In this section, we will be using Tableau to learn concepts on data outliers, seasonality effect, and the relationships and impacts. There is no R coding in this lab session.

Setup

This worksheet will be used to capture your images from Tableau and to share your observations. Example of capturing and including an image is included at the end of this sheet for your reference. You will need to log onto Tableau and Connect/Import the file EuroStore.xls found in the ‘bsad_lab10’ folder.

Remember to always set your working directory to the source file location. Go to ‘Session’, scroll down to ‘Set Working Directory’, and click ‘To Source File Location’. Read carefully the below and follow the instructions to complete the tasks and answer any questions. Submit your work to RPubs as detailed in previous notes.

Note

For your assignment you may be using different data sets than what is included here. Always read carefully the instructions on Sakai. Tasks/questions to be completed/answered are highlighted in larger bolded fonts and numbered according to their particular placement in the task section.

Task 1: Data Outliers and Seasonality Effect

First get familiar with the data and what each columns represent. A description of the data is provided in a seperate sheet called ‘Desc’ in the same Excel file. Refer to Lab05 for early exercise using Tableau.

In a new Tableau sheet

1A) Plot Sales (Rows) versus Week (Columns). Include a snapshot here. Analyse the data source and explain in clear words the behavior you observe.

This graph shows that there is a drastic drop in sales during week 23 to $22,824. For weeks before and after weeks 23-25, there were small increases and decreases in sales value, but no large fluctuations.

1B) Switch from SUM(Sales) to Average AVG(Sales). Change the Sales scale to be more reflective of the data. Include a snapshot here. Explain the new behavior relative to 1A).

Compared to the behavior in graph 1A, the data is being averaged rather than added together. When the data is averaged and scaled, it is clear that large fluctuations in sales are prresent throughout the year. The data is better represented and visualized in this format since it does a good job at showing large fluctuations in sales. The scale range is adjusted to 19-29k, rather than 0-25k (which was misleading). ##### 1C) Add Temp to the Color scale found in Marks. Change SUM(Temp) to AVG(Temp). Edit the color legend to be more reflective of hot and cold temperatures. Include a snapshot here. Explain the combined behavior of sales and temperature.

The combined behavior of sales and temperature show that sales are greater when temperature is higher.

Task 2: Relationships and Impacts

In a seperate Tableau sheet

2A) Plot Sales (Rows) versus TV (Columns). Switch both measures from SUM() to Dimension. The plot should look more like a scatter plot. Include a snapshot here. Explain the behavior of Sales versus TV. How much you think is the upper limit amount that should be invested in TV ads?

It does not seem like there is much correlation between increased sales from tv advertisements. The behavior of the plot shows that even with 0 ads, sales are still generated. I would say the upper limit for tv ads is 90k since after that amount, there are no significant changes in sales.

2B) Overlay Radio to the previous plot using the Size. scale found in Marks. Include a snapshot here. Explain how the additional Radio ads to Tv ads is impacting Sales.

By adding the radio overlay, it is clear that there is greater correlation with sales.

In a separate Tableau sheet

2C) Plot Sales versus Fuel Volume. Explain behavior.

There is a positive correlation with sales and fuel volume; sales increases with additional fuel volume.

2D) Overlay Temperature using the Color scale. Follow 1C) for temperature settings. Explain the new combined behavior and the impact of temperature.

When the temperature is high, fuel volume is usually higher, as well as sales.

2E) Overlay Holiday using the Label scale. Include a snapshot here. Explain the new combined behavior and the impact of Holiday.


Seems like there are higher fuel volume needs during a holiday, and higher sales.

In a separate sheet

2F) Use a Tree Map to best show the combined effect of Sales, Fuel Volume, Temp, and Holiday. A sample view is shown below. Consider using the Quick Filter on Holiday and Temp to isolate and better view the impact of each. You can have more than one filter at a time. Include a snapshot here.
2G) Write a small paragraph summarizing your final conclusions on what you think most affect Sales and under what conditions.

I think temperature and holidays affect sales the most. The greatest sales amounts occurred almost always when temperature was high and there was also usually a holiday. TV and Radio ads do not have as great of an affect on sales.