Investments Analysis

The following tasks were given by Refocus. I was a data analyst working for a company planning to venture into a new market involving financial services. In line with this, it is requesting insights on sources of financing companies tap into when entering the said industry. Decision-makers will use insights from the report created for their alternatives analysis as they explore probable sources of financing to start offering the new service.

file: investment_subset.csv

Data Preparation

I first created a new table that has a new column called ‘market_FS’ for market with only Financial Services and another column called ‘country’ based on country code.

create table investment_subset_backup as
select *,
case
	when market='FincialServices' then 'Financial Services' 
	end as market_FS,
case 
	when country_code = 'USA' then 'United States of America'
	when country_code = 'RUS' then 'Russia'
	when country_code = 'ESP' then 'Spain'
	when country_code = 'IND' then 'India'
	when country_code = 'SGP' then 'Singapore'
	when country_code = 'LVA' then 'Latvia'
	when country_code = 'BWA' then 'Botswana'
	when country_code = 'CHN' then 'China'
	when country_code = 'GBR' then 'United Kingdom'
	when country_code = 'JPN' then 'Japan'
	when country_code = 'DUE' then 'Germany'
	when country_code = 'FRA' then 'France'
	when country_code = 'CAN' then 'Canada'
	when country_code = 'POL' then 'Poland'
	when country_code = 'HKG' then 'Hong Kong'
	when country_code = 'ARG' then 'Argentina'
	when country_code = 'ITA' then 'Italy'
	when country_code = 'CHE' then 'Switzerland'
	when country_code = 'LTU' then 'Lithuania'
	when country_code = 'BRA' then 'Brazil'
	end as country
from investment_subset

I deleted market column from new table.

ALTER TABLE investment_subset_backup
DROP COLUMN market

I deleted rows of new table where market_FS is null.

delete from investment_subset_backup
where market_FS is null

I deleted rows that have under null funding_total_usd.

delete from investment_subset_backup
where funding_total_usd is null

Finally, I deleted rows that have under null funding_total_usd.

UPDATE investment_subset_backup
SET status='unknown'
WHERE status IS NULL; 

UPDATE investment_subset_backup
SET country_code='unknown'
WHERE country_code is NULL

UPDATE investment_subset_backup
SET country = 'unknown'
where country is NULL

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Descriptive Analysis

With the data prepared, I wrote a query that gives me a descriptive analysis that presents the number of observations of companies operating in financial services.

SELECT round(AVG(seed),2) as avg_seed,MAX(seed) as max_seed,min(seed) as min_seed
FROM investment_subset_backup

Output

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Data Exploration

Aware of the reality that equity crowdfunding is a bit rare in financial services, I had to determine whether or not there has been aprevious instance where a startup offering financial services received equity crowdfunding. If there was, I had to provide details of the company such as the country it operates in, the year it was founded, its status (whether or not it is still operating), and the amount of equity crowdfunding it acquired.

select country,founded_year,status,equity_crowdfunding
from investment_subset_backup
where equity_crowdfunding>0

Output

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Outliers

I had to determine whether or not a significant outlier in terms of total funding (USD) exists among companies that offer financial services. If there was, I had to provide details pertaining to this outlier such as its country, status, year founded, and total funding (USD).

Select * 
from investment_subset_backup
where funding_total_usd is not null
Order by funding_total_usd desc

Select country,founded_year,status,funding_total_usd
from investment_subset_backup
where funding_total_usd is not null
And funding_total_usd>110000000

Output

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Data Visualization

For presenting data, I had to first excluding the significant outlier from the dataset. The visualization would need to provide insights on the company in terms of the usual financing sources for businesses that offer financial services. This was done by exporting the data from SQL to MS Excel to utilize the necessary graphs that would present the average funds acquired from financing sources such as equity crowdsourcing, undisclosed sources, convertible notes, debt financing, and private equity.

delete from investment_subset_backup 
where funding_total_usd = 725000000

Output

Conclusion

According to the graph above, we can see that the average funds from equity crowdfunding exceeds more than half the average acquired funds from other financial sources. We can say that for start-up companies under Financial Services have been getting their funding mostly from equity crowdfunding than other means.