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.

There is no clear evidence that the sales are increasing or decreasing. We notice a trend of fluctuations except the time during 23rd to 25th weeks, where we notice a severe drop in sales to approximately $22K

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).

There’s a trend of fluctuations of the sales within $20K - $25K and there is no noticeable drop in sales but we can say that it reaches the highest between weeks 17 and 32

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.

We notice that when the sales reached the highest, it was during hotter temperature, and that the colder it gets, the lower the sales

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 are definitely more sales that take place when the total volume of target audience reached in GRP units is 0. I don’t think it is possible to tell the upper limit amount that should be invested in TV ads because the TV is not expressed in dollars.

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.

It looks like the total radio GRPs along with TV total volume of target audience reached in GRP have a strong correlation to higher sales

In a separate Tableau sheet

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

Both sales and Fuel volume have a positive relationship as when one increases, the other increases as well

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

It looks like the hotter the temperature, the more fuel volume recorded resulting in higher sales. And the colder the temperatures, the lower the fuel volume recorded resulting in lower sales.

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

During holiday seasons when the temperature is hotter, the fuel volume recorded and sales are usually higher

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 tree map reconciles neatly with the scatter plot as they both show data consistency. They both show positive relationship between the variables, the higher the temperature, the higher fuel and sales recorded during holidays.However, we can say that the fuel volume and the hot tempreture have the most affect on sales.