Is Your Company's Data Too Messy to Sell or License to AI?
AITrainingDataBroker.com
Is your company's
data too messy
to sell or license?
Duplicates, half-empty fields, files named final_v3. Here is what AI companies care about.
Jimmy Lin
Is your company's data too messy to sell or license?
Hello, everyone. When I talk to owners about licensing their data to AI companies, one worry comes up more than any other.
They tell me their data is a mess, with duplicate contacts, half-empty fields, and decisions buried in old email threads.
If that sounds like your company, this video is for you, because messy data is far more common than you might think.
We will look at what AI companies actually look for, and at when a mess really is too much.
The video
Full script
Hello, everyone. When I talk to owners about licensing their data to AI companies, one worry comes up more than any other.
They tell me their data is a mess, with duplicate contacts, half-empty fields, and decisions buried in old email threads.
If that sounds like your company, this video is for you, because messy data is far more common than you might think.
We will look at what AI companies actually look for, and at when a mess really is too much.
Let me start with some research. A study published in Business Horizons in 2020 looked at 75 data quality checks across a wide range of organisations.
On average, 47% of newly created data entries had at least one critical error, such as a wrong number or a missing field.
Only 3% of the checks met the standard the managers themselves called acceptable.
In other words, almost every company's data is messy, so yours is in good company. Before we go further, let me tell you who I am.
I'm Jimmy. I have worked in data at Fortune 500 companies, as a data analyst, a data engineer and a software engineer, and I am trained in data science. I am also a Canadian military veteran, where I specialized in data analysis and reporting.
Are you selling your data? We are your broker and technical advisor. We get you the best price, and we guide your team through the technical side, so your data stays private.
Are you buying data for an AI lab? We find the right data for you and see it through to delivery, so you can focus on advancing AI research.
So what does a messy company look like? Usually it is the same customer entered 3 times, with half the fields left empty.
Files have names like final, version 3, real, and the important decisions were made in email instead of in the system.
Many companies also moved from an old system to a new one years ago, and some data came across badly.
On top of that, notes are full of typos and shorthand that only your team understands, and all of that is normal.
Here is the key idea of this video: messy and missing are 2 very different problems.
Duplicates, typos, empty fields and data spread across several tools are messy, and that can be cleaned up and matched.
What is hard to fix is data that is missing, such as no record of how the work ended, only a few months of history, or work kept mostly on paper.
AI companies care most about the trail of the work and how it ended, far more than about perfect, tidy fields.
Take a staffing agency with 40 people. A client emails asking for 5 forklift drivers to start by Monday.
A recruiter screens 12 people in a spreadsheet full of shorthand, with 2 of them entered twice, and makes calls and notes along the way.
In the end, 4 are sent to the client and 3 are hired, and 90 days later, 2 are still on the job.
The spreadsheet is a mess, but every step and the outcome are there, and that is exactly what makes the data useful.
The good news is that you do not have to clean any of this up before talking to anyone, because that is part of my job.
We merge duplicates into one record, and we match the same piece of work across email, files and your other systems.
Then we de-identify your data, giving each person the same stand-in name everywhere, so the story still holds together.
Finally, we sort it by type and year and describe what is inside, so an AI company can see what it is getting.
To be fair, sometimes the data really is not enough, and you should know the signs.
It is hard when fewer than 30 people work at desks, or when there is less than 2 years of history.
It is also hard when no outcome is written down anywhere, when the work is mostly on paper, or when most of it is held for clients and is not yours to license.
If none of those apply to you, a messy system is not a reason to rule yourself out.
So bring the mess, and I will help you sort it out, as your broker and technical advisor.
As your broker, I bring your data to several AI companies and AI labs, get you competing offers, and work through the terms with you, and you make the final call.
As your technical advisor, I guide your team through the export, then handle the clean-up, the matching and the de-identification.
The clean-up costs you nothing up front, because I am paid from the deal itself, and only when it closes.
To wrap up, a messy system is normal, and what matters is that the work and how it ended are written down somewhere.
If you run a company with 30 or more people, the data you already have could become a new revenue stream. You can find out if yours qualifies, for free, at AITrainingDataBroker.com.
If you have further questions, leave them in the comments, and I will answer them in the next video.
Thank you for watching, and I will see you next time.
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