What is the ‘Unstructured Data’ conundrum?
If your organization struggles to corral and analyze unstructured data, you’re not alone. In a recent survey, only 18% of organizations in a reported being able to take advantage of such data.
Great majority of data is unstructured information (almost 90 percent of it) like text, video, audio, web server logs, social media, and more. Organizations who figure out how to use it will get a definitive competitive advantage.
So, What is Unstructured Data?
Unlike structured data — which is organized in a searchable format, like a database, unstructured data is information, in many different forms, that doesn't follow conventional data models, making it difficult to store and manage in a mainstream relational database.
Is it a big problem?
Here is where it gets interesting: Unstructured data is majority of the existing data, it is also the vast majority of new data being generated today. The complicating factor is that Unstructured data has an internal structure but it does not contain a predetermined data model or schema. It can be textual or non-textual. It can be human-generated or machine-generated.
What are the most common types of unstructured data?
One of the most common types of unstructured data is text. Unstructured text is generated and collected in a wide range of forms, including Word documents, email messages, PowerPoint presentations, survey responses, transcripts of call center interactions and posts from blogs and social media sites. Other types of unstructured data include images, audio and video files.
Yet another type of data is Machine data, one that's growing quickly in many organizations. For example, log files from websites, servers, networks and applications yield a trove of activity data. Data from sensors on manufacturing equipment and other connected devices is yet another form of unstructured data.
Has unstructured data been harnessed by anyone successfully?
The industries that were ahead in processing of unstructured data were retail and finance since in the mid-2000s, retailers were the first to combine and analyze data from customer emails, images, voice, and store-traffic records to market to particular customers. And in the last few years, finance has made substantial progress as well. Other industries, including shipping, transportation, legal, and real estate, are now leaning into unstructured data.
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