The volume and variety of data is exploding, and the race is on for organizations to make better sense of it all. Still, many organizations are struggling to drive value from their unstructured data. Semantic technologies can help companies understand all of their data and the value of it, and enable insights that were not available before. Businesses are also using semantic technologies to unearth precious nuggets of information from vast volumes of data and to enable more flexible data use. Semantic data analysis is about identifying the meaning and tone in unstructured text.
"Unstructured data is becoming more critical to manage for the purpose of completing a business process or to provide better customer support," said Steve Butler, general manager of artificial intelligence platform provider AI Foundry. "People are reading and processing unstructured documents, but if you can automate that, you can save money and improve customer support."
Semantic technology isn't new, but it's rapidly gaining momentum as more companies attempt to compete with data. Semantic technology has always been about the meaning of data, its context, and the relationships between pieces of information. Recruiting and job search site CareerBuilder has been using semantic technologies for more than a decade to improve the relevance of job and candidate searches. Recently, the company acquired a majority stake in semantic recruitment-technology company TextKernel to fortify its semantic search and data analytics capabilities.
[See 14 Ways IoT Will Change Big Data and Business Forever.]
"If you think about semantic search, it's not what you type, it's what you mean. The relevancy has always got to be there," said Matt Ferguson, CEO of CareerBuilder. "What we're trying to do is maintain the highest level of relevancy while shortening the time [necessary to find a job or fill a position]."
Some organizations are using semantic technologies to overcome the limitations of rules-based systems and ordinary keyword search, since both of those exclude that which was not explicitly defined.
"Analysts are concerned about the freshness and completeness of data [as well as] the merging of structured and unstructured data. People want to be able to understand the context of their data and what questions they can ask of it. They [also] want flexibility in the way they're looking at data and asking questions of it," said Sean Martin, CTO and founder of smart data platform provider Cambridge Semantics.
Click through to see some examples of what you can do with semantic technologies. Then tell us what you think in the comments.
**Elite 100 2016: DEADLINE EXTENDED TO JAN. 15, 2016** There's still time to be a part of the prestigious InformationWeek Elite 100! Submit your company's application by Jan. 15, 2016. You'll find instructions and a submission form here: InformationWeek's Elite 100 2016.