Solutions for Unstructured Data That Includes Video
If you’ve landed on this page, there’s a good chance you’re sitting on a mountain of unstructured data, specifically an abundance of video files. Your goal is to parse, organize, and distribute the information in such a way that makes it the most useful to the greatest number of people in your organization. But unstructured data can be as unruly and difficult to manage as a bag of snakes. So the question becomes: How can you tame it?
What’s the Problem With Unstructured Video Data?
So what’s the problem with unstructured data? As is the case with a tangle of wires, the hurdle with unstructured data is that it’s difficult to classify, manage, organize, and distribute. And ultimately, what’s the use of collecting loads of information if you can’t do anything with it? When videos are tossed into the mix, things become even more complicated because they’re not easily searchable in text-based database systems.
But before you can develop a plan to sort out the mess, you must define the data goals. Ask yourself a few key questions such as:
- Who needs access to the information?
- For what are they using it?
- How does the intended data use support the company’s overarching goals?
Unstructured Video Data: Indexing
Indexing is a database optimization technique, which preprocesses information and allows for faster querying. It’s an advanced database administration skill that requires the programmer to account for many options, like missing values and form errors.
When videos are in the data mix, indexing is even more complicated. However, by setting up a simple save-and-catalog function, it’s manageable. So how do you do it?
First, save the video file on the network. Make sure it’s somewhere accessible to the people who will need it. Also, ensure that people can’t change file names easily. If they do, it can “break” the database. Then, catalog each A/V file by including GUID keys that point to where they sit on the network.
If greater specificity is needed, make a record — and corresponding line item — for each video frame. Yes, it’s time and labor-intensive, but the effort is often worth it to mine intelligent data.
Unstructured Video Data: Metadata
After creating the index, the next step is gathering, storing, and linking the appropriate metadata, which may include the date, length format, EXIF info, and source. Cataloging the metadata is vital because it provides a searchable and filterable field for the video file line item.
Sometimes, you may want to write some metadata to the file name as a backup. You can achieve this by structuring the file names like [DATE]_[GUID].mp4. By doing so, team members can quickly determine to which record the line item is tied.
Let’s Discuss Your Unstructured Data Needs
Outsourcing database logistics to a third party can be the ideal solution because it frees up internal resources for profit-generating activities. Plus, partnering with database experts can decrease costs associated with employment.
Inzata Analytics’s team has considerable experience empowering businesses, non-profits, schools, and government entities to maintain their unstructured databases. Reach out today. Let’s start the conversation.