When folks in IT circles hear the term “unstructured data management,” they likely think about how best to store the mountains of unstructured data in their organizations. But there’s another aspect to unstructured data management that relates to how companies can best automate, analyze and visualize unstructured data in order to extract business value from it.
It’s a huge issue because companies have huge amounts of unstructured data; estimates put it at 80% to 85% of all data in most organizations. So, yes, that does create significant storage challenges, including how best to classify the data, determine how frequently it’s accessed and, consequently, the most cost-effective place to store it. Plenty has been written about those topics, including these fine pieces at SearchStorage and ComputerWeekly.
But one of the key reasons for storing unstructured data in the first place is because it’s becoming more and more valuable. That’s because artificial intelligence tools are emerging that help companies extract value from unstructured data. (To learn more about unstructured vs. structured data, check out this previous post.)
Tapping into unstructured data
Previously, unstructured data was beyond the reach of business intelligence tools, which generally can only ingest and analyze highly structured data, such as that in a relational database. The advent of AI is changing that equation, giving rise to a new form of unstructured data management, one that has to do with how to turn unstructured data into a structured format that business intelligence and analytics tools can understand – effectively enabling them to analyze unstructured data.
Tools such as the Indico Unstructured Data Platform employ AI technologies including deep learning, machine learning, transfer learning and natural language processing. It is also built on top of a database of some 500 million labeled data points, enough to give the platform context behind most any type of unstructured data, from Word documents to images and video.
Related Article: Unstructured Data Analytics – RPA Fails & Intelligent Automation Succeeds
Automate, analyze and visualize unstructured data
Companies use the platform to “read” their unstructured data just as an employee would. This gives companies the ability to automate unstructured data processing as well as analyze and visualize the data to gain valuable insights.
In terms of automation, the Indico platform enables intelligent document processing. Companies can now automate document-intensive processes that traditionally required employees to read documents and manually extract key data. The same employees who actually perform the work use the Indico Data platform to build models to automate processes, such as by extracting key data from unstructured documents and inputting it into downstream CRM, ERP or other systems.
The platform can also be used to convert unstructured data into a structured format that’s compatible with your business intelligence tools, such as Microsoft Power BI and Google’s Looker. Now you can unlock years’ worth of insights from your unstructured data and apply BI to gain newfound insights.
Similarly, Indico’s intelligent process automation platform can be used to prepare unstructured data to be used with data visualization tools such as Tableau, which likewise requires data to be in a structured format.
Creating unstructured data analytics tools
Indico Data essentially turns all of these BI and visualization platforms into unstructured data analytics tools, by giving you the ability to automate the process of turning unstructured data into a format they can understand. No more do you need armies of employees poring over your unstructured data looking for useful nuggets. Indico Data can reduce the resources required for the job by about 80%, enabling you to finally make good use of your unstructured data.
Learn more about how the Indico Unstructured Data Platform can help you with unstructured data management by registering for our free trial.
