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When 80% of the World's Data Is Unstructured, Entity Extraction is a Must
August 11, 2017 | Entity Extraction
According to the International Data Corporation, an incredibly small portion of the world’s data is ever actually analyzed, reaching a grand total of less than 1%. Even worse, Gartner research predicts that data volume will grow 800% over the next five years, and up to 80% of that data will be completely unstructured. Unstructured data consists of web pages, legal documents, images, medical records, mobile content, and other types of rich media that consumers and businesses are producing every second.
Large amounts of unstructured data can cause serious problems for modern data centers, but on a simpler level, it’s a tremendous waste. The increasing amount of unstructured data is also causing problems for businesses who need to comply with a growing web of regulations. With structured data, these businesses could easily manage databases and gain new insights.
The problem of exponentially growing unstructured data volumes may seem daunting, but the solution is actually quite simple: better entity extraction tools.
Entity Extraction: How It Works
Due to the exponentially increasing volume of unstructured data in the world, it is literally impossible for humans, even the most skilled data scientists, to manually process all this information. However, it isn’t impossible for a software program.
For large volumes of unstructured information to be useful, they must first be turned into structured data. The best way to structure this information is to use entity extraction software to automatically identify semantic concepts (person names, organization names, places, monetary amounts, dates, and more) that can be associated with the source document as metadata. This structured metadata can then be used to enhance a variety of applications such as searching, data visualization, and trend analysis.
To get the most insight from such data, entity extraction is fast becoming one of the most powerful forms of text analytics used today. Of course, not all entity extraction tools are created equally.
What to Look for in Entity Extraction Tools
Because it is impossible for humans to manually inspect and analyze large amounts of data efficiently, the software used to perform these tasks must be extremely reliable. If a single misspelling or unknown word can derail named entity recognition software, then it’s not a particularly useful tool.
Before investing in entity extraction software, make sure it has the following capabilities:
- Accurate software that minimizes the number of missed entities (recall) and extraneous entities (precision)
- Incredibly fast
- Highly scalable
- Flexible enough to support third party tools
- Multilingual capabilities
- Available through the cloud (SaaS) and on premise
NetOwl’s Extractor product can provide all of these things. By using the most advanced entity extraction tools, it turns unstructured data into semantic concepts and actionable insight.
With entity extraction technology, the future of structured data is clear.