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Unstructured data is more challenging and expensive to manage than structured data. Learn how to find a better data solution.
Key takeaways- Unstructured data makes up much of big data and includes emails, social-media data, text files and more.
- Unstructured data is more expensive to store and nearly impossible to search through
- The right data-management solution will equip organizations with better tools to use data
What is unstructured data?
Any information could be unstructured data: text, images, webpages, and audio and multimedia files. This data isn’t designed to be stored within a database, and it’s not arranged through a data model. Some estimates claim up to 90% of big data is unstructured, and the amount of information only continues to grow. Common data types include email messages, text files (Word documents), mobile data (text messages), photos, videos, social media and website information. Additionally, Internet of Things (IoT) data, such as sensor information, is unstructured. Artificial intelligence, machine learning and digital-surveillance tools also generate unstructured data.How is unstructured data impacting data storage?
Unstructured information creates chaos for institutional data storage. Big data’s unstructured properties make efficient data management nearly impossible. Here are a few challenges that unstructured data present for organizations:Issues with relational databases
Structured data is typically kept in a relational database (RDBMS). It’s categorized with different types of fields, like personal information or ZIP codes. Structured data is much easier to manage because you can search for it in databases, and it’s created and stored in a preset manner. RDBMS can’t store unstructured data because databases and most software can’t recognize and process it according to set structures. It’s expensive and difficult to classify and store unstructured data. It usually needs to be pulled from its source, altered, and stored in another database to be useful.Massive storage requirements
Unstructured data takes up enormous storage space within databases, and being unable to find or analyze data when it’s needed creates big unnecessary expenses for organizations. Primary and secondary data-storage solutions must be robust to back up all that data.Compliance with PII regulations
Unstructured data may create issues with personally identifiable information (PII). There are laws and regulations surrounding this type of data; if an organization doesn’t comply, it could face costly consequences. It can be hard to determine if there’s PII within unstructured data.Sharing challenges
For many organizations, data must be accessible and sharable. It’s much more challenging to share and collaborate with unstructured data; PII-compliant sharing is extremely expensive and time-consuming.How does unstructured data management work?
With all the issues unstructured data creates, organizations need a better solution to manage it. This means being able to:- Gather it
- Store it
- Search it
- Share it
- Analyze it
- The data models are more flexible; organizations can alter the database as needed
- They make it easier and faster to search unstructured data
- They’re easier for developers and programmers to use
- The amount of data to be transferred
- How important scalability is to your organization
- Which processes can be automated
- How easy the interface is to manage and navigate
- The price and fee structure
- Whether it offers all the services you need, i.e., data indexing
