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Project: Analyzing Unicorn Companies
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  • Did you know that the average return from investing in stocks is 10% per year (not accounting for inflation)? But who wants to be average?!

    You have been asked to support an investment firm by analyzing trends in high-growth companies. They are interested in understanding which industries are producing the highest valuations and the rate at which new high-value companies are emerging. Providing them with this information gives them a competitive insight as to industry trends and how they should structure their portfolio looking forward.

    You have been given access to their unicorns database, which contains the following tables:

    dates

    ColumnDescription
    company_idA unique ID for the company.
    date_joinedThe date that the company became a unicorn.
    year_foundedThe year that the company was founded.

    funding

    ColumnDescription
    company_idA unique ID for the company.
    valuationCompany value in US dollars.
    fundingThe amount of funding raised in US dollars.
    select_investorsA list of key investors in the company.

    industries

    ColumnDescription
    company_idA unique ID for the company.
    industryThe industry that the company operates in.

    companies

    ColumnDescription
    company_idA unique ID for the company.
    companyThe name of the company.
    cityThe city where the company is headquartered.
    countryThe country where the company is headquartered.
    continentThe continent where the company is headquartered.

    The output

    Your query should return a table in the following format:

    industryyearnum_unicornsaverage_valuation_billions
    industry12021------
    industry22020------
    industry32019------
    industry12021------
    industry22020------
    industry32019------
    industry12021------
    industry22020------
    industry32019------

    Where industry1, industry2, and industry3 are the three top-performing industries.

    Unknown integration
    DataFrameavailable as
    df
    variable
    WITH top_industries AS (
    SELECT 
    	industry,
    	COUNT(*) AS num_comp
    FROM industries
    JOIN dates 
    USING(company_id)
    WHERE EXTRACT(year FROM date_joined) IN ('2019', '2020', '2021')
    GROUP BY industry
    ORDER BY num_comp DESC
    LIMIT 3
    ), 
    
    top_valuations AS ( 
    SELECT 
    	industry,
    	EXTRACT(year FROM date_joined) AS year,
    	COUNT(*) AS num_unicorns,
    	AVG(valuation) AS average_valuation
    FROM industries 
    JOIN funding USING(company_id) 
    JOIN dates USING(company_id)
    GROUP BY industry, year
    )
    
    SELECT 
    	industry,
    	year,
    	num_unicorns,
    	ROUND(AVG(average_valuation/1000000000), 2) AS average_valuation_billions
    FROM top_valuations
    WHERE year IN (2019, 2020, 2021) 
    	  AND industry IN (SELECT industry
     	 	               FROM top_industries)
    GROUP BY industry, year, num_unicorns
    ORDER BY year DESC, num_unicorns DESC;