How to Deal With Video and Unstructured Data: Content Tagging
Working with unstructured video data can be extremely difficult to tame! But don’t worry. With a few handy tips, the process becomes a lot more manageable.
Please note: this is our second article in a series on unstructured data. Click here to read the first installment, which explores indexing and metadata.
What Is the Problem With Unstructured Data?
Unstructured information is an unwieldy hodgepodge of graphic, audio, video, sensory, and text data. To squeeze value from the mess, you must inspect, scrub, and sort the file objects before feeding them to databases and warehouses. After all, raw data is of little use if it cannot be adequately leveraged and analyzed.
What Is Content Tagging?
In the realm of information management, content tagging refers to the taxonomic structure established by an organization or group to label and sort raw data. You can think of it as added metadata.
Content tagging is largely a manual process. In a typical environment, people examine the individual raw files and prep them for data entry. Common tasks include:
- Naming each item
- Adding meta descriptions of images and videos
- Splicing videos into frames
- Separating and marking different mediums
How to Use Content Tagging to Sort Unstructured Data
You can approach content tagging in several ways. Though much of the work is best done manually, there are also ways to automate some processes. For example, if an incoming file ends with a .mov or .mp4 suffix, you can write a script that automatically tags it as a video. The same can be done for graphics and text documents.
Tagging helps organize unstructured data as it provides readable context atop which queries can be crafted. It also allows for pattern establishment and recognition. In fact, photo recognition programs are, in large part, fueled by extensive tagging.
The Pros and Cons of Content Tagging
Tagging has its pros and cons. The downside is the manual labor involved. Depending on the amount of inbound data, it could take considerable resources to get the job done. Many businesses prefer to enlist third-party database management teams to mitigate costs and free up personnel.
As for pros, there are a couple. Firstly, content tagging makes data organization much more manageable. When you label, sorting becomes a snap. Secondly, tagging adds more value to data objects, which allows for better analysis.
We Can Transform Your Unstructured Data
Leveraging AI-powered tools to perform complex data management tasks can save you money and increase efficiency in the long run. Inzata Analytics maintains a team of experts that focuses on digital data, analytics, and reporting. We help businesses, non-profits, and governments leverage information technology to increase efficiency and profits.
Get in touch. Let’s talk. We can walk you through the advantages of AI-powered data management and how it can boost your bottom line. See a demo of the platform here.