post

December 20, 2021

Data Management Trends

Home > Blog > Data Management Trends

Reliably extracting information from unstructured data!

Maybe you’ve heard the truism that 80 percent of business-relevant information lives in unstructured form. Whether the figure is accurate or not, it’s hard to argue that a whole lot of unstructured data lives in chats, e-mails, reports, articles, and recorded conversations. The ability to contextualize and reliably extract information from this kind of data presents a huge opportunity. Instead of storing information in tables where the types of data, labels and categories must be predicted by a developer, it can be mined in it’s raw, unstructured form, eliminating the need for complex schematics and database architects.

If you want to create a bio sketch of someone in your organization, you can use all of the unstructured data relating to that person in order to add detail (i.e. their dog’s name is Leo, they like to have the day after their birthday off of work).

Constant movement = constant data

We’ve talked about graphDB but not about the various scenarios in which they become an accelerator. When it comes to event tracking, graph DB can turn static, individual pieces of data into a flow of information tracking, capturing multimedia records of movement and mapping patterns.

In a basic real-world scenario, a security guard working the night shift at a local business is surrounded by cameras. Instead of simply funneling live feeds to a TV, these cameras collect every object that appears, including the guard, and analyze them via blockchain algorithms. Based on patterns of movement over the course of several days, an IDW can recognize when the guard gets up to refill his cup of coffee mid-shift. The ecosystem that connects the cameras to the blockchain algorithms is also connected to a coffee machine that makes sure a fresh hot pot is waiting for them in the break room.

More importantly, the cameras analyze general movement around the building and identify suspicious behavior based on prior security reports. With all of this information readily available, the security system is able to generate its own security reports, highlighting patterns of movement during specific times and flagging moments that should be reviewed by a human.

Stay up to date

Subscribe and receive updates on what we are reading, writing and other stuff going in the worlds of OneReach.ai