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This repository contains an ETL project for crowdfunding data, utilizing Python and SQL technologies. The data is extracted and transformed with Pandas and Python, and loaded into a PostgreSQL database using pgAdmin, providing clean and organized data for analysis.

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theidari/Crowdfunding_ETL

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Crowdfunding platforms like Kickstarter and Indiegogo have been growing in success and popularity since the late 2000s. From independent content creators to famous celebrities, more and more people are using crowdfunding to launch new products and generate buzz, but not every project has found success. To receive funding, the project must meet or exceed an initial goal, so many organizations dedicate considerable resources looking through old projects in an attempt to discover “the trick” to finding success.

Project Overview

  • Objective:The instructions for this project are divided into the following subsections:

    • Create the Category and Subcategory DataFrames
    • Create the Campaign DataFrame
    • Create the Contacts DataFrame
    • Create the Crowdfunding Database
  • Methods, Software and Attribution:

    • following programming languages, software, and libraries were used in this project:

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    • The project header GIF has been designed by powerpoint and photopea.com using assets from Freepik.com.

ETL Results

  • Create the Category and Subcategory DataFrames
Fig[1]: Category and Subcategory DataFrames

 

  • Create the Campaign DataFrame
Fig[2]: Campaign DataFrame

  • Create the Contacts DataFrame
Fig[3]: Contacts DataFrame

Fig[4]: Crowdfunding ERD

References
[1] Trilogy Education Services, a 2U, Inc. brand.

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This repository contains an ETL project for crowdfunding data, utilizing Python and SQL technologies. The data is extracted and transformed with Pandas and Python, and loaded into a PostgreSQL database using pgAdmin, providing clean and organized data for analysis.

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