SQL to Track Startups, IPOs, and More: Crunchbase Enterprise with Snowflake

During 2020, more than 500 companies in the data and analytics space were acquired all over the world. Can you guess the top three cities where these companies are based?

Number three is London, number two is New York. And number one is San Francisco, where 33 companies in the data analytics space were acquired in 2020.

Now, how can you get access to the raw data behind this analysis? Well, there is a company that tracks the crazy world of mergers, acquisitions, and IPOs. It’s Crunchbase, and they have compiled an incredible dataset of companies, investors, funding data, and the key people behind all of this. What I love about Crunchbase is that they want to make this data available to everyone.

They offer this dataset on their website and you can access most of it for free. If you want to go deeper, you can get a pro subscription, but what if you want full access to this data updated daily in the Data Cloud? Well, Crunchbase is already available in the Snowflake Data Marketplace. All you need to do is go to your Snowflake account, find the Crunchbase listing and request access to the premium dataset. Once Crunchbase approves your request, you will find the data right there, updated daily, with no hassles. That’s the power of the Data Cloud.

That’s how I ran my queries and found out that Crunchbase tracks around 8,000 companies acquired during 2020. 7% of these companies are in the data and analytics space:

2018 vs 2020 trends

Comparing the trends between 2018 and 2020:

• There were way less acquisitions tracked this year, compared to 2 years ago.
• Health Care, Financial Services, and Science & Engineering acquisitions went up in the rankings.
• Manufacturing, and Media & Entertainment went down.

Diversity in boards

And we can keep going deeper. For example, how many of these companies have a female board member? Only 16%, which is better than 2010, when that number was 9%.

But let’s talk about the possibilities. Once you have this data inside Snowflake, you can explore it with SQL, apply your favorite visualization tools to visualize it, or link it with your Salesforce data to empower your sales processes.

The possibilities are endless, and the Data Cloud is here to help.

Queries

Companies acquired during 2020 per category

select sum(price_usd), count(*) c, cat.value category
from acquisitions a
join organizations b
on a.acquiree_uuid=b.uuid
  , table(split_to_table(category_groups_list, ',')) cat
 where acquired_on between '2020-01-01' and '2021-01-01'
group by category
order by 2 desc nulls last;

Data & Analytics companies acquired 2020 per city

-- Data & Analytics companies aquired 2020 per city
select sum(price_usd), city, country_code, count(*) c --, acquiree_name, acquirer_name, city
from public.acquisitions a
join organizations b
on a.acquiree_uuid=b.uuid
where acquired_on between '2020-01-01' and '2020-12-31'
and category_groups_list like '%Data and Analytics%' 
group by 2, 3
order by c desc

Percentage of acquired companies with a female board member

with acquired_da as (
    select price_usd, acquiree_name, acquirer_name, city, acquiree_uuid
    from public.acquisitions a
    join organizations b
    on a.acquiree_uuid=b.uuid
    where extract(year from acquired_on) = 2010
    and category_groups_list like '%Data and Analytics%' 
)select female_board_member, count(*) c, c/sum(c) over() percent
from (
    select org_name, boolor_agg(gender='female')::varchar female_board_member
    from (
        select person_name, org_uuid, gender, org_name
        from jobs a
        join people b
        on a.person_uuid=b.uuid
        join acquired_da c
        on a.org_uuid=c.acquiree_uuid
        where job_type = 'board_member'
    )
    group by 1
    order by 2
)
group by 1
;

Closing thoughts

With these queries you can see how easy is to connect the dots between what’s happening in the industry and what matters to you. For this post, I focused on the Data & Analytics space, but there’s a lot more to discover.

I’ll keep adding more interesting findings on the Crunchbase dataset to following Twitter thread — please chime in with your thoughts:

Want more?

I’m Felipe Hoffa, Data Cloud Advocate for Snowflake. Thanks for joining me on this adventure. You can follow me on Twitter, and check reddit.com/r/snowflake for the most interesting Snowflake news.