Unstructured Data In Big Data

Make productive use of your unstructured data with MongoDB

Before the modern day ubiquity of online and mobile applications, databases processed straightforward, structured data. Data models were relatively simple and described a set of relationships between different data types in the database.

Unstructured data, in contrast, refers to data that doesn’t fit neatly into the traditional row and column structure of relational databases. Examples of unstructured data include: emails, videos, audio files, web pages, and social media messages. In today’s world of Big Data, most of the data that is created is unstructured with some estimates of it being more than 95% of all data generated.

As a result, enterprises are looking to this new generation of databases, known as NoSQL, to address unstructured data. MongoDB stands as a leader in this movement with over 10 million downloads and hundreds of thousands of deployments. As a document database with flexible schema, MongoDB was built specifically to handle unstructured data. MongoDB’s flexible data model allows for development without a predefined schema which resonates particularly when most of the data in your system is unstructured.

To learn more about what MongoDB can do for your organization around managing unstructured data, download our white paper today.

Companies ranging from startups to Fortune 500s choose MongoDB to build, scale, and innovate.

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