Unstructured data is data that doesn’t fit neatly in a traditional database and has no identifiable internal structure. This is the opposite of structured data, which is data stored in a database. Up to 80% of business data is considered unstructured, with this number increasing year over year.
Examples of unstructured data are text documents, e-mail messages, photos, videos, photos, presentations, social media posts, and more.
Unstructured data usually does not include a predefined data model, and it does not match well with relational tables. Text heavy, unstructured data may include numbers and dates, as well as facts. This leads to difficulty in identifying this data using conventional software programs.
Unstructured data is becoming the bulk of the data in an organization – studies show that 70-80% of all data today is unstructured. Documents, audio files, video files, log files, genomics data, seismic data, engineering design data, and virtualization files are examples of unstructured data.
The expense of managing huge volumes of unstructured data generated within an organization can lead to higher expenses.
What to know about unstructured data:
- Volume: The sheer quantity of data will continue to grow in a incomprehensible rate
- Velocity: The quantity of data is coming in at a continually faster rate
- Variety: The types of data continue to be more varied