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Mining for Hidden Gold with Unstructured Data

by SwoopTalent, on April 16, 2018

What if 90% of your hiring data was missing?

A hiring manager wouldn't ask potential applicants to submit 10% of their work experience on their resume, right? Certainly not 10% of their phone number or email address! But when an application is submitted for an open position, only about 10% of the data is stored in any usable form. A submission form that properly sorts data inputs into specific tables will do a good job of saving that data for analysis, but what about the cover letter? What about the skills section of the resume? Aside from maybe a specific, formatted list of skills, it's unlikely that any of that data will be usable in an aggregate form. So, if 90% of data isn't pulled into the hiring process, how can you find it?

Structured vs. Unstructured Data

Structured data is the type that fits easily into predefined categories and is easily captured. Structured data can include name, email, telephone number, maybe graduation year and College Degree, if the form is sufficiently advanced. Unstructured data is everything else. The content of the cover letter, most of the resume, blog posts, etc. Unstructured data is more challenging to process, but that's really where the gold is. To extract the value from unstructured data they must be analyzed with respect to their meaning and context. The signal-to-noise ratio of unstructured data makes it difficult to constructively process, which is why so many ignore it. We at SwoopTalent, however, embrace the challenge.

When it comes to making hiring decisions, more information is always better. Having more information about a hire can pay huge dividends for decades down the line.

The SwoopTalent Factor

At SwoopTalent, we're experts at extracting the information from unstructured data and providing it in a useful format.

Our technologies include semantics, Natural-Language Processing (NLP), and no shortage of other techniques. Combined, these techniques are known as Artificial Intelligence and Machine Learning. They can make the hiring process straightforward and much more informed. 

If you're interested in applying our advanced techniques to your hiring data and improving your hiring quality, please don't hesitate to contact us.

Topics:finding talentsourcing in techtalent poolstalent insightshiringHRrecruiting

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