This week’s #workoutwednesday by Ann Jackson was to prepare dataset using Tableau Prep then to design visualisation to show customers spend more on their first or second purchase.

The list of full requirements can be found here but on a high level:

  • Create a dataset using Tableau prep which will return customer level first and second order information with regards to sales, no. of categories and no. of products sold in the order
  • Dataset will have 9 columns i.e. Customer id, 1st Purchase Date, 2nd Purchase Date, 1st Purchase Sum Sales, 2nd Purchase Sum Sales, 1st Purchase # Categories, 2nd Purchase # Categories, 1st Purchase # Products, 2nd Purchase # Products
  • Create scatter plot with First purchase sales vs second purchase sales with 2 strip plots
  • Sheets aligned in dashboard using float method

It was good reason to try out Tableau prep for first time and create the dataset for the challenge. Here is how my workflow looked like in Tableau prep:

developing the viz was pretty straight forward with scatter and strip plot but the tricky part was to arrange all the sheets into float order with pixel perfect output. Took a bit of time to arrange but was able to make it at last. Overall, enjoyed working on Tableau Prep. I will be writing on Tableau prep in coming days to explain how it works.

Here is my output for the challenge (Click on Image for interactive version)

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This week’s #workoutwednesday by Rody Zakovich was about playing with dates. challenge was about comparing current period with previous period of same range of days.

Requirements:

  • User can select a Start and End date for the Current Period
  • The “Previous Period” contains the same number of days as the Current Period, and ends the Day before the Start Date
  • Both the “Current” and “Previous” Periods must be on the same Date Axis (No dual Axis!)
  • The Current Period must be distinguishable from the previous period
  • Must show the Current Period Range, as well as, the Prior Period Range

This week data uses the superstore dataset

Here is my solution with the requirements given:

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This week’s #workoutwednesday was about a problem that can only be solved using table calculations. Idea was to find which city contributes the most sales to each states.

Requirements

  • Use only table calculations
  • The bar length is the total sales of each state
  • City must be included in the view.
  • Display only one mark per state.
  • Label each bar by the city with the highest sales, sales for that city, and the total sales for that state.
  • No level of detail calculations allowed.

This week uses the superstore dataset.  You can get it here at data.world

Below is my attempt to design solution with the above requirements:

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This week’s #workoutwednesday was about building frequency matrix using color to represent the frequency intensity.

Requirements

  • Use sub-categories
  • Dashboard size is 1000 x 900; tiled; 1 sheet
  • Distinctly count the number of orders that have purchases from both sub-categories
  • Sort the categories from highest to lowest frequency
  • White out when the sub-category matches and include the number of orders
  • Calculate the average sales per order for each sub-category
  • Identify in the tooltip the highest average spend per sub-category (see Phones & Tables)
  • If it’s the highest average spend for both sub-categories, identify with a dot in the square
  • Match formatting & tooltips – special emphasis on tooltip verbiage

This week uses the superstore dataset.  You can get it here at data.world

Below is my attempt to meet the above requirements:

Thanks for reading 🙂

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This week’s #workoutwednesday was about comparing last 2 periods sales for a sub-category using date functions with customize tooltips.

Requirements

  • Dashboard size should be 1000×600.
  • Sub-Category on the Rows Shelf, and Year of Order Date on the Columns Shelf
  • There are 3 measures, Sales, % of Total (in year) and % Difference
  • Only the Sales Measure has color (which colors you use don’t matter, just that Sales is the only measure colored).
  • Users can select a Year and a Measure and sort the table in Descending order by that measure in that year.

Dataset used was superstore dataset available with Tableau

Below is my attempt to meet the above requirements:

Thanks for reading 🙂

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