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Did you know that the average return from investing in stocks is 10% per year! But who wants to be average?!
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. |
SELECT * FROM companiesWITH top_industries AS
(SELECT industry
FROM public.dates
INNER JOIN public.funding
USING(company_id)
INNER JOIN industries
USING(company_id)
WHERE EXTRACT(YEAR FROM date_joined) BETWEEN 2019 AND 2021
GROUP BY industry
ORDER BY COUNT(company_id) DESC
LIMIT 3),
yearly_rankings AS
(SELECT industry,
EXTRACT(YEAR FROM date_joined) AS year,
COUNT(company_id) AS num_unicorns,
ROUND(AVG(valuation)/1000000000, 2) AS average_valuation_billions
FROM dates
JOIN industries
USING(company_id)
JOIN funding
USING(company_id)
--WHERE (EXTRACT(YEAR FROM date_joined) BETWEEN 2019 AND 2021)
GROUP BY industry, year
ORDER BY industry, year DESC)
SELECT * FROM yearly_rankings
WHERE industry IN (SELECT * FROM top_industries) AND year BETWEEN 2019 AND 2021;SELECT industry, COUNT(company_id)
FROM public.dates
INNER JOIN public.funding
USING(company_id)
INNER JOIN industries
USING(company_id)
WHERE EXTRACT(YEAR FROM date_joined) BETWEEN 2019 AND 2021
GROUP BY industry
ORDER BY COUNT(company_id) DESC
LIMIT 3