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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_indus AS (
SELECT industries.INDUSTRY,COUNT(industries.company_id)
FROM industries INNER JOIN dates on industries.company_id = dates.company_id WHERE EXTRACT(YEAR FROM dates.date_joined) BETWEEN 2019 AND 2021 GROUP BY industries.industry ORDER BY count(industries.company_id) DESC LIMIT 3
)
SELECT ind.industry,EXTRACT(year FROM date_joined) as year,count(ind.company_id) num_unicorns,round(avg(valuation/1000000000),2) as average_valuation_billions
FROM public.industries ind
INNER JOIN funding fn
ON fn.company_id = ind.company_id
INNER JOIN public.dates da
ON da.company_id = ind.company_id
INNER JOIN top_indus ti
ON ti.industry = ind.industry
WHERE EXTRACT(YEAR FROM da.date_joined) BETWEEN 2019 AND 2021
GROUP BY ind.industry,EXTRACT(year FROM date_joined)
ORDER BY year DESC,num_unicorns DESC