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Engineered the required data for the data analysis from AWS S3 bucket into a citus database and came up with a dash web app with insights: Cookie Churn Analysis, Geographic mapping, Top level meta categories, User’s favourite category, Top channels, Machine Learning model(SVM) to predict a user’s click on Ad.

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retazo0018/C1X-INTERN-PROJECT

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Dash Web App

Components of this Web App

  • C1x Logo with SOKA INSIGHTS tab

  • ValueBoxes:

    • Total Number of Unique Users
    • Total Capacity
    • Total Impressions
    • Total Clicks
  • DatePicker DropDown Menu:

    • One can choose from a range of dates between June 5th, 2019 to June 11th, 2019 and can also choose a cumulative option of 'all the 7 days' By default, the cumulative option is chosen and displayed. Affects the 'Top Level MetaCategories' graph and the 'Most Liked Channels' graph.
  • Top Level MetaCategories:

    • Finding the top 10 metacategories whose advertisements are most clicked on by the ShopClues customers.
  • Most Liked Channels:

    • Finding the number of unique users for each channel type, to identify the preferred medium.
  • Cookie Age Trend:

    • Percentage age trend of the cookies over the week.
  • Geographic Segmentation:

    • Displays the geographic positions of all the ShopClues users using their ip address.
  • Screenshots of the web app

    • GitHub Logo

    • GitHub Logo

    • GitHub Logo

About

Engineered the required data for the data analysis from AWS S3 bucket into a citus database and came up with a dash web app with insights: Cookie Churn Analysis, Geographic mapping, Top level meta categories, User’s favourite category, Top channels, Machine Learning model(SVM) to predict a user’s click on Ad.

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