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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 three As (Select i.industry, Count(d.company_id)as num_unicorns
From public.dates as d
Join public.industries as i On d.company_id=i.company_id
Where EXTRACT(year from d.date_joined) in (2019, 2020, 2021)
Group By i.industry
Order By num_unicorns Desc
Limit 3)
Select i.industry, EXTRACT(year from d.date_joined)As year, Count(d.company_id)As num_unicorns,
Round(Avg(f.valuation/1000000000), 2)As average_valuation_billions
From public.dates as d
Inner Join public.funding as f On d.company_id=f.company_id
Inner Join public.industries as i On d.company_id=i.company_id
Right Join three as t On i.industry=t.industry
Where EXTRACT(year from d.date_joined) in (2019, 2020, 2021)
Group By i.industry, EXTRACT(year from d.date_joined)