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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.
Spinner
DataFrameas
df
variable
--Determining the three best-performing industries based on the number of new unicorns created between 2019 and 2021.
SELECT 
	industry,
    COUNT(*) AS number_of_unicorns
FROM industries AS i
INNER JOIN dates AS d
	ON i.company_id = d.company_id
WHERE EXTRACT(YEAR FROM d.date_joined) IN (2019, 2020, 2021)
GROUP BY industry
ORDER BY COUNT(*) DESC
LIMIT 3;

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The three industries that saw the greatest number of unicorn companies being created between 2019 and 2021 were Fintech, Internet software & services, and E-commerce & direct-to-consumer.

The change in the number of companies becoming unicorns over 2019-2021 is shown by the chart below.

Current Type: Bar
Current X-axis: industry
Current Y-axis: num_unicorns
Current Color: year

Number of Companies that became Unicorns between 2019-2021

The number of E-commerce & direct-to-consumer, Fintech, and Internet Software & Services companies that became unicorn companies was not drastically different between 2019 and 2020. In 2021, however, all three industries experienced a large increase in the number of companies that became unicorns.

The increased number of unicorn companies implies that, unless a proportionally large increase in the number of investors or capital invested in E-commerce & direct-to-consumer, Fintech, and Internet Software & Services companies also occurred, the average valuation of the companies that became unicorns in 2021 is likely to be lower than previous years. This is supported by the following table.

Spinner
DataFrameas
df
variable
--Determining the number of unicorns and average valuation (in billions) 
--for each of the top 3 industries for each year between 2019 and 2021.
WITH top_industries AS
(
    SELECT 
    	i.industry, 
        COUNT(i.*)
    FROM industries AS i
    INNER JOIN dates AS d
        ON i.company_id = d.company_id
    WHERE EXTRACT(year FROM d.date_joined) in ('2019', '2020', '2021')
    GROUP BY industry
    ORDER BY count DESC
    LIMIT 3
),

yearly_rankings AS 
(
    SELECT 
    	COUNT(i.*) AS num_unicorns,
        i.industry,
        EXTRACT(year FROM d.date_joined) AS year,
        AVG(f.valuation) AS average_valuation
    FROM industries AS i
    INNER JOIN dates AS d
        ON i.company_id = d.company_id
    INNER JOIN funding AS f
        ON d.company_id = f.company_id
    GROUP BY industry, year
)

SELECT 
	industry,
    year,
    num_unicorns,
    ROUND(AVG(average_valuation / 1000000000), 2) AS average_valuation_billions
FROM yearly_rankings
WHERE year in ('2019', '2020', '2021')
    AND industry in (SELECT industry
                    FROM top_industries)
GROUP BY industry, num_unicorns, year, average_valuation
ORDER BY industry, year DESC
Current Type: Bar
Current X-axis: industry
Current Y-axis: average_valuation_billions
Current Color: year

Average Valuation for Unicorn E-commerce, Fintech, and Internet Software Companies 2019-2021

The average valuation for unicorn companies in 2021 was lower across all three industries but their overall trends from 2019-2021 were not the same.

The e-commerce & direct-to-consumer companies had very similar average valuations in 2019 and 2021 at 2.58 and 2.47 billion, respectively. This suggests that the increased average valuation in 2020 may have been an outlier event.

The average valuations of fintech companies decreased consistently between 2019 and 2021, dropping from 6.8 billion to 2.75 billion. Whether this trend continues into 2022 seems to depend, at least in part, on whether similar growth as seen between 2020 and 2021 in the number of unicorn companies continues.

The internet software & services industry saw very similar average valuations between 2019 and 2020, coming in at 4.23 and 4.35 billion, respectively. 2021 marked the largest year-over-year percentage drop of any industry, falling approximately 50.3%.