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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
Column | Description |
---|---|
company_id | A unique ID for the company. |
date_joined | The date that the company became a unicorn. |
year_founded | The year that the company was founded. |
funding
Column | Description |
---|---|
company_id | A unique ID for the company. |
valuation | Company value in US dollars. |
funding | The amount of funding raised in US dollars. |
select_investors | A list of key investors in the company. |
industries
Column | Description |
---|---|
company_id | A unique ID for the company. |
industry | The industry that the company operates in. |
companies
Column | Description |
---|---|
company_id | A unique ID for the company. |
company | The name of the company. |
city | The city where the company is headquartered. |
country | The country where the company is headquartered. |
continent | The continent where the company is headquartered. |
The output
Your query should return a table in the following format:
industry | year | num_unicorns | average_valuation_billions |
---|---|---|---|
industry1 | 2021 | --- | --- |
industry2 | 2020 | --- | --- |
industry3 | 2019 | --- | --- |
industry1 | 2021 | --- | --- |
industry2 | 2020 | --- | --- |
industry3 | 2019 | --- | --- |
industry1 | 2021 | --- | --- |
industry2 | 2020 | --- | --- |
industry3 | 2019 | --- | --- |
Where industry1
, industry2
, and industry3
are the three top-performing industries.
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
ORDER BY year DESC, num_unicorns DESC