Did you know that the average return from investing in stocks is 10% per year (not accounting for inflation)? 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. |
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.
-- CTE to get the top performes in 2019, 2020 and 2021
WITH top_performers AS (
SELECT
B.industry AS industry,
COUNT(A.company_id) AS company_count
FROM
dates A
JOIN
industries B ON A.company_id = B.company_id
WHERE
EXTRACT(YEAR FROM A.date_joined) IN (2019, 2020, 2021)
GROUP BY
B.industry
ORDER BY COUNT(A.company_id) DESC
LIMIT 3
),
-- CTE to get average valuation for each industry and year
yearly_rankings AS (
SELECT
B.industry AS industry,
EXTRACT(YEAR FROM A.date_joined) as year,
COUNT(A.company_id) AS num_unicorns,
AVG(C.valuation) as average_valuation
FROM
dates A
JOIN
industries B ON A.company_id = B.company_id
JOIN
funding C ON A.company_id = C.company_id
GROUP BY
B.industry, EXTRACT(YEAR FROM A.date_joined))
-- FINAL QUERY
SELECT
industry,
year,
sum(num_unicorns) AS 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_performers)
GROUP BY
industry, year
ORDER BY
year DESC, num_unicorns DESC