Data Analysis in Tableau

Data analysis is best done with visualizations. Color, shapes, and images help our brains to make sense of the underlying patterns within a dataset. Without the ability to see the patterns, we are unable to make informed decisions.

For this analysis, I pulled down a free online retail store dataset from Kaggle. I cleaned up the dataset in Tableau Prep prior to importing it into Tableau Desktop. In Prep, I grouped similar item categories, cleaned up text (removed numbers, punctuation, and fixed casing), and added Level of Detail calculations and rankings.

Once in Tableau Desktop, I created my visualizations. These included:

  • A Pearson Correlation Matrix of product categories sold
  • Customer Segmentation (K-means clustering) scatter plot and map
  • Sales forecast
  • Sales ranking by country
  • Sales time heat map

Once all visualizations were complete, I did finishing touches for the tooltips, text formatting, color agreement, and then assembled the dashes.

Tableau allows the user to interact dynamically with the dashes through filters, highlights, and tooltips.

Explore my completed Tableau Workbook demo in Tableau Reader.

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