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Project: Analyzing Unicorn Companies
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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:

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 i.industry,
COUNT(i.*) AS count
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 i.industry, year
ORDER BY year, i.industry
)

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
This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.