The Age of Video Big Data
With video as the current king of content, videos will be the next frontier of Big Data and a new source of business intelligence. Video has the power to give us information about how we interact with the world unlike any other form of data source. More importantly, video content is exploding!
So the real question is... how can we extract value from all these videos?
However, video data is very difficult medium to work with. There are a few good reasons why:
- There are so many elements inside a video (speech, text, faces, objects, etc)
- It is not static.
- It is very difficult to extract the various elements of video data.
- Each video element requires a different data extraction technique.
- It is very difficult to make sense of video data because of its unstructured nature.
- It's expensive to extract data at scale
Only a few years ago, all of the above would be impossible to deal with. But now, with extensive use of Artificial Intelligence (A.I.), we are able to extract various kinds of video data, analyze and transform these unstructured to structured video big data to unlock patterns, trends, and relationships to gain business intelligence, and eventually actionable items.
The above is the typical process how we extract and transform videos into business intelligence using Video Big Data.
To find out how we can help you unleash the true potential of your videos by using Video Big Data, contact us!
What video data can we extract?
Video Big Data is dependent on the kind of data that we can extract from videos. The following is a list of video data elements that you select, so that we can extract according to your needs:
- Speech (in 12 languages)
- Text (over 25 languages)
- Objects (over 20,000 objects)
- Motion (entire or specific zone of video frame)
- Face ( (Unique face identification)
- Emotions (up to 8 major emotions)
- Offensive content
Depending on the selected video element, the extracted data can be presented in both unstructured and structured data format.
For video data extracted for Objects, Motion, Face, Emotions and Offensive Content, the results are presented in English. However, we can pass these data through an translation process and present these results in over 100 languages.