Welcome to the High-Growth Companies Analysis project repository! In this project, we delve into trends among high-growth companies to provide valuable insights for an investment firm. By analyzing data on unicorn companies, we aim to identify top-performing industries and understand their valuation dynamics over time.
Did you know that the average return from investing in stocks is 10% per year? However, who wants to settle for average returns? Our task is to support an investment firm by analyzing trends in high-growth companies. We will explore the unicorns database, which contains information on companies' founding dates, valuations, funding, and industries. By understanding which industries produce the highest valuations and the rate at which new high-value companies emerge, we aim to provide our client with a competitive edge in structuring their investment portfolio.
The dataset includes the following tables:
- dates: Contains information on the company's founding date.
- funding: Provides details on the company's funding rounds.
- industries: Includes the industry in which the company operates.
- companies: Contains information on the company's location and name.
We use PostgreSQL for data analysis, employing SQL queries to extract insights from the dataset. Our analysis focuses on identifying the top-performing industries based on the number of new unicorns created over specific periods and understanding their average valuations.
- notebook.ipyn: Notebook containing the PostgreSQL queries used for data analysis and commentary.
- README.md: You are here! Provides an overview of the project.
DataCamp Workplace project link: https://github.com/NonsoOmoko/Project-Analyzing-Unicorn-Companies/blob/648484d8b9a2c63075156a0a18d7b9c164671cb2/DataCamp%20Project%20Workplace%20Link