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My Amazon Spending

Analysis of personal Amazon purchases made in 2020, utilizing a Tableau dashboard to explore and visualize various aspects of the data.

Skills Used

Challenge

I initially assumed data acquisition would be a simple one-click download from Amazon. However, requesting large amounts of data took approximately two weeks to retrieve my personal Amazon history. Additionally, Amazon's nested subcategory structure meant the 'Product Category' column didn't accurately categorize products. This required manually categorizing each product to ensure properly structured data for effective visualization and analysis in Tableau.

Results

I should clarify that I don't use Amazon Prime exclusively—I share it with 10 other people. The $4,500 spent wasn't just my shopping; it was very much a group effort. I found it interesting to see which friends use the account more than I do. It's important to note this occurred during lockdown when online shopping became a primary activity for many people. I was building my first personal computer during this period, which is reflected in the 'Most Popular Categories' chart.

Process

Understanding Requirements

Given that I had such a large dataset, it was important to hone in on what exactly I wanted to achieve. Understanding the requirements beforehand made it easier to narrow my scope into the relevant parts of the data

Data Cleaning

Removal of unnecessary columns and missing values. Standardizing the report for tabular analysis

Exploratory Data Analysis

Created some basic charts to understand the distribution of the data and identify outliers. I also found errors in my data entry during the categorization process in some rows (i.e. Books was spelled Bookss)

Data Visualization

Designed the overall template in Figma to ensure the dashboard follows design principles. Calculated custom measures within Tableau to better understand spending

We conducted user interviews, surveys, and analyzed in-app analytics to understand the pain points and user needs. We also studied competitor apps and industry trends to gather insights

Understanding Requirements

Data Cleaning

Removal of unnecessary columns and missing values. Standardizing the report for tabular analysis

Exploratory Data Analysis

Data Visualization

Designed the overall template in Figma to ensure the dashboard follows design principles. Calculated custom measures within Tableau to better understand spending

We conducted user interviews, surveys, and analyzed in-app analytics to understand the pain points and user needs. We also studied competitor apps and industry trends to gather insights

Understanding Requirements

Data Cleaning

Removal of unnecessary columns and missing values. Standardizing the report for tabular analysis

Exploratory Data Analysis

Data Visualization

Designed the overall template in Figma to ensure the dashboard follows design principles. Calculated custom measures within Tableau to better understand spending

We conducted user interviews, surveys, and analyzed in-app analytics to understand the pain points and user needs. We also studied competitor apps and industry trends to gather insights

Understanding Requirements

Data Cleaning

Removal of unnecessary columns and missing values. Standardizing the report for tabular analysis

Exploratory Data Analysis

Data Visualization

Designed the overall template in Figma to ensure the dashboard follows design principles. Calculated custom measures within Tableau to better understand spending

We conducted user interviews, surveys, and analyzed in-app analytics to understand the pain points and user needs. We also studied competitor apps and industry trends to gather insights

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