Part 1 (Q1-Q4, 9 points) Instruction: Please submit 4 Tableau Flow files (.tfl) and 1 Word file on Brightspace and name them properly. There are many students submitting many files, bad naming took me time to fix and will get point deduction. This assignment asks you to use Tableau Prep to re-arrange data from several worksheets inAssignment5_SuperstoreData.xlsx.
I have FOUR questions, and each expects you to do a Tableau Flow file, that will achieve the results in the table below. Your submission file should be named as Your output should look like the csv files on Brightspace Q1 Assignment5_Q1_LastName_FirstName.tfl Assignment5_Q1.csv Q2 Assignment5_Q2_LastName_FirstName.tfl Assignment5_Q2.csv Q3 Assignment5_Q3_LastName_FirstName.tfl Assignment5_Q3.csv Q4 Assignment5_Q4_LastName_FirstName.tfl Assignment5_Q4.csv Note that, the column orders of your .csv files do not matter as long as you have correct data and proper naming (I have explained in the slides). When I grade, I will just import your ‘.tfl’ file on my computer with Assignment5_SuperstoreData.xlsx as the source data.
The output data from your flow files should be similar to my .csv files (except the column order may be different). Those whose outputs are the same as the .csv files I provide will get 100% of the grade. Please DON’T submit your .csv files, I don’t need them. In the Excel file, there are 8 tabs, Oct, Nov, and Dec tabs are sales order data from the last 3 month in 2019. Returns tab contains the returned order records; Customer has customer related information based on “Customer ID” and their sales totals from 4 quarters in 2018; Return Reasons tab contain 8 different reasons of return based on Returns datatab; Product has product related information; and Region contains the state-region match information. You are expected to do some works in Tableau Prep that may include: union, join, step (data cleaning), pivot, aggregate, and output, …, to accomplish the assignment. In addition, you may also need to change variable type properly (number, string, date, geographic, …) to reflect their true properties, filter data with certain criteria, and remove redundant variables correctly from union/join operations. From the instructions below, you should know which type of join or union to choose.
Q1. (3 points) Please merge all three months data together and join them with Returns, Customer and Product data. All records (rows) from three months should remain in the final outputs, but the data from other 3 datasets are included when they match. The output should look like Assignment5_Q1.csv.
Q2. (4 points) Please merge all three months data and You should add a variable (calculated field) called ‘Total Payment,’ which equals “Quantity Ordered New”*”Unit Price”*(1- “Discount”) + “Shipping Cost”. After that join the merged 3-month dataset with Customer and Region data. All records (rows) from Customer data should remain and the order data from customers in those 3 months should be aggregated (sum) when the Customer ID is matched. Please only contain (filter) customers from “East” and “South” regions. The output should look like Assignment5_Q2.csv.
Q3. (3 points) Please use only Nov Sales data and join them with and Returns and Return Reasons data. All records (rows) from the filtered Return data should remain and the order data from Nov should be included when they are matched. Then, please filter all sales orders by Reason Category that is either “Inaccurate product description” or “Defective item or item does not work”. The output should look like Assignment5_Q3.csv.
Q4. (5 points) Please use Customer data inner-JOINING with sales data from Oct, Nov and Dec tabs, and pivot their sales from four quarters in 2018. After that, please aggregate the total sales value of 2018 in a new column called “2018 Annual Sales” and join back to the original set. Please exclude those customers that have “2018 Annual Sales” smaller than $500.00. The output should look like Assignment5_Q4.csv.
Q5 (1 point) Please submit this as “Assignment5_Q5_ LastName_FirstName.docx”. In this question, you will submit and ‘scratches’ of your final project presentation. You start with an ‘overview’ of your final dashboard (or stories) and follow with several detailed ‘scratch’ for each dataviz (which can be a worksheet or a dashboard if you do a Tableau story). Please provide some description of each ‘scratch’ as they form a storyline. The grading criteria for this question will be based on the dataviz principles in module 5-1. If you have had some preliminary dataviz works in Tableau Desktop, you can just capture some screen shot and paste those images files in order. If you have not imported your data to Tableau Desktop, please use Word “shapes” as markup elements that explain how your personal story will be presented. Grading Criteria (Questions 1-4): The number of correct variables in your final output based on your .tfl files. The number of rows of data in your final output based on your .tfl files. The order of variables in your output does not matter.
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