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.

IN THIS VIZUALIZAITON, THE SUM OF WEEKLY SALES IS DEPICTED OVER 50+ WEEKS. THERE APPEARS TO BE A SIGNIFICANT DROP IN SALES IN WEEKS 23-25. THIS DROP CORRECTS AS THE WEEKS PROGRESS.

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).

IN COMPARISON TO WEEK ONE, THIS VIZUALIZATION SHOWS THE AVERAGE SALES (RATHER THAN THE SUM) VOLUME OVER THE SAME NUMBER OF WEEKS IN 1A. USING THE SALES AVERAGE IN THIS CASE CORRECTS THE SIGNIFICANT SALE DROP DISPLAYED IN VIZUALZATION 1A AND MAKE THE GRAPH MOST CONSISTENT

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.

USING THE TEMPERATURE SENSITIVE COLORING OPTION THIS OBSERVER IS ABLE TO SEE THE RELATIONSHIP BETWEEN AVERAGE SALES VOLUME AND TEMPERATURE. THIS VISUALIZATION SHOWS THAT AN INCREASE IN TEMPERATURE GENERALLY LEADS TO AN INCREASE IN THE AVERAGE SALES VOLUME.

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?

ANSWER: THERE IS NOT A GOOD/SIGNIFICANT INDICATION OF A RELATIONSHIP BETWEEN TV AND SALES… WE PICKED CHOSE TO INVEST 90 IN TV ADVERTISEMENT ON AN ARBITRARY BASIS

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.

ANSWER: THIS VISUALIZATION SHOWS THAT AN INCREASE IN RADIO ADVERTISEMENT SPENDING LEADS TO A SIGNIFICANT INCREASE IN THE AMOUNT OF SALES.

In a separate Tableau sheet

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

THIS SCATTER PLOT INDICATES A RELATIONSHIP BETWEEN HIGHTENED SALES AND AN INCREASE IN FULE VOLUME - AS FUEL VOLUME INCREASES, STORE SALES INCREASE AS WELL.

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

HIGHER TEMPRATURE CONTRIBUTES TO HIGHER FUEL VOLUME AND HIGHER SALES - TEMPERATURE AND FUEL VOLUME ARE CORRELATED AND THEREFORE TEMPERATURE IMPACTS SALES - WHEN WEATHER CONDITIONS ARE GOOD (WARM) PEOPLE BUY MORE GAS AND THIS RESULTS IN HIGHER STORE SALES.

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

THERE ARE MORE HOLIDAYS/TRAVEL TIME IN THE SUMMER, PROBABLY BECUSE IT IS WARMER DURING THE SUMMER. AS SUCH, STORE SALE INCREASE AROUND THE HOLIDATS BECAUSE PEOPLE HAVE MORE TIME TO DRIVE, REFULE, AND BUY FROM THE STORE…

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.

GIVEN THE VISUALISATIONS ABOVE, IT IS CLEAR THAT HOLIDAYS AND WARMER TEMPERATURE CONTRIBUTE TO HIGHER FUEL CONSUMPTION. THIS IN TURN INCREASES STORE TRAFFIC WHICH DRIVES STORE SALES VOLUME HIGHER. IN CONCLUSION HOLDAYS AND WARM WEATHER ARE IMPORTANT CONTRIBUTORS TO HIGH STORE SALES FOR THIS GAS STATION AND POSSIBLY GAS STATION IN GENERAL.