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Artificial Intelligence: Turning Unstructured Data into Strategic Information
Unstructured data has long been the Achilles heel of data management. It’s the information stored in text documents, videos, audio, social media, and logs. Unlike the structure and easy searchability provided by data stored in databases, unstructured data follows no specific template or pattern, making it difficult to interpret. A rough estimate is that 80 to 90 percent of all data in an organization is unstructured. The fact that data is unsearchable restricts its usability within an organization.
Artificial Intelligence, particularly Natural Language Processing (NLP), provides a foundation for building tools that can tap into unstructured data to extract information.
Mikey Shulman, head of machine learning at Kensho, said that “because structured data is easier to work with, companies have already been able to do a lot with it. But since most of the world’s data, including most real-time data, is unstructured, an ability to analyze and act on it presents a big opportunity.”
Marco Varone, chief technologist at expert.ai, said that “the amount of value hidden in unstructured, textual information is so large that every enterprise needs to define a strategy to transform language into data in a coherent and scalable way. It is not simple, and it takes time, effort, and investment to achieve, but it is no longer possible to postpone this decision as the risk of being left behind in the digital world is becoming bigger every day.”
Althea Davis, Chief Data Officer at Abu Dhabi Digital Authority, said that “the integration of [unstructured] data goes beyond tactical. [It makes it possible to turn] data into strategic information.”
