I was working late a few days ago on desciphering some data some clients sent us, and I was scrolling down endless Excel tables and CSV foles with various cryptic codes, all caps product names and a bunch of digits that didn't really make sense at first glance.

I was thinking "it can't be that all this gibberish has any value, has it? I could randomly generate something similar and it will look the same for somebody just looking at it for the first time"

If I would put the original client sent data file alongside a randomly generated file with similar structure, somebody could not have guessed reliably which one was the real one and which one was fake.

But somehow, that file was valuable enough for our clients to pay us to clean it, transform it, ingest it into our systems and then export it to some of their external systems where they receive all their 3rd party data.

And then it hit me: why is data so valuable?

Data is operations

For many businesses, data is the building block of their operations. Everything that moves within their company, has a digital fingerprint and needs to be properly managed as well.

If the digital system gets out of sync from their physical ones, then their business starts to lose money: stock goes missing, orders fail to go out, wrong prices on the website means lost revenue, etc.

This is the most fundamental type of data one business has: data that is used for the day to day operations and keeping it tidy and consistent is their biggest priority.

Data is knowledge

For other businesses, there's a second layer of data: quantitative data gathered along the way that can outline trends.

This data is ingested, is taken inside some algorithms and some charts get produced. These charts then go on management's desks and based on what they see there, they make decisions.

Are there colors that grow in popularity? Then we should stock up on that.

Are there stores that under-perform? Then we need to investigate what isn't running properly there.

Is there a growing trend of returns? What is missing from our website that make clients send a lot of the things they buy, back?

Many questions can be answered from that data, but first you need to know what the questions are and what data can give you the answers.

Data is money

For many companies, data is also money. And not because they sell it (although there are many that do that), but because they can unlock new ways to increase their revenue.

They collect data, clean it up and based on its nature, they can utilize it to make more money.

For example, collecting email addresses allows companies to build a new client funnel they can contact directly and promote to them almost for free.

Other companies can crawl publicly available data and build certain databases that can then be sold to other interested companies.

There are literal ways to turn data into money, but you need to figure out what opportunities are out there, and how valuable that data is.

Conclusion

Most companies are in the "Data is operations" and "Data is knowledge" phases and are currently building solutions to aid them in that area.

Sometimes it can be even simple ERP systems or Google Sheet tables that are shared between the employees, or more complex dedicated systems that can move industrial quantities of data.

But nevertheless, technology is available to enhance either one of them. You just need to ask the right questions