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.

From week 1 to week 23, the sales is increasing. However,there is a sharp drop of sales from week 23-25. The data might have go wrong or have miss data. After week 25, the sales go back to the normal range which is slowly decreasing.

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).

This graph gives a better representation of the sales and week. The axis of the sales has changed to average of sales, this can have more accurate conculsion. Moreover, this graph still show a sudden drop on the sales at week 33-36 which does not match to the previous graph. ##### 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.

When added the temperature into the graph, we can know that as the temperature goes up the sales goes up. The is a relationship between sales and the temperature. As the temperature is lower, the sales is also lower.

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?

There is a relationship between sales and TV. We can see that as we spend more on TV advertisment, the sales go up. The upper limit amount should be 90000. ##### 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 radio to the graph, we can see that there is a relationship between these two. The trend is very similar to the tv and sales. Therefore, when spending more on TV and radio advertisment can have an increase in sales. However, the spending should not go over 90000. In a separate Tableau sheet

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

AS the sales goes upm the fuel volume goes up as well. They are moving toward the same direction which means that it might have positive correlation. ##### 2D) Overlay Temperature using the Color scale. Follow 1C) for temperature settings. Explain the new combined behavior and the impact of temperature. As the temperature goes up, the fuel amount is also in a higher range. When the temperature is lower, the fuel volume is also in a lower range. During the warmer temperature, the sales and fuel volume increased. People tend to go out and consumer more during the warmer temperature.

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

When it is hoilday, people tend to make more purchase and this will lead to more fuel amount. Also, people often have more activities during hoilday, this can become one of the factor that lead to increase in sales and furl volume

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.

The factors that affect sales can include temperature and advertisment. The suggestion for this company is to advertise more during summer which temperature is warmer where people tend to purchase more during warmer weather. People tend to buy more during hoildays vs non hoilday. From the treemap we can see that the hotter days have higher sales volume. Therefore, more advertising during the summer months can increase sales espacially during the hoildays in the summer times.