Unstructured data lacks a predefined model or structured format commonly seen in traditional databases, making it raw and unorganized, often in various formats. It cannot be stored in a traditional relational database or database system.

Unstructured data is often text heavy, but also can include dates, numbers or even audio or images. Examples of unstructured data include business documents, videos, emails, and audio files.

Vs. Semi-Structured Data

While semi structured data also does not adhere to the data models associated with relational databases it does contain tags or markers that can enforce field hierarchies within the data sets.

The nature of unstructured data make it difficult to parse compared to data stored in standard databases. While estimates vary depending on source, unstructured data is generally considered to make up a large percentage, if not outright majority, of all data in existence today.

Snowflake and Unstructured Data

Snowflake is bringing accelerated time-to-value to unstructured data, enabling customers to store, govern, process, and share files as they do with structured and semi-structured data. To learn more, download our eBook, “Best Practices for Managing Unstructured Data” or watch our webinar on-demand, Start Using Unstructured Data in Snowflake.