Any document, file, image, report, form, etc. without a highly defined data model or relational structure for convenient use in automated processing; unstructured data may contain many facts: fields, dates, names etc., but not organized in the rows and columns associated with structured data.


newsEnterprise content management and mortgage automation solutions expand Unisys’ SaaS offerings
NewsEditLive! allows embedded WYSIWYG editor and ability to embed social media in custom apps
profileAyasdi seeks to enable business users without specialized training to analyze and discover meaningful patterns in large, complex data sets
NewsAcquisition of the data integration provider strengthens enterprise content integration and “smart process applications” strategies, a wise move, says Forrester analyst
Information Management's DM RadioYou’ve seen the projections: a severe shortage of data scientists is at hand, threatening our ability to leverage big data. At the same time, research continually pushes the state of the art in machine learning and pattern/similarity search algorithms. More and more technology companies are claiming to leverage advanced algorithms to eliminate the need for dedicated data scientists. Coming full circle, we hear arguments that you not only need data scientists but you also need to balance the skills of an entire big data team comprised of technologists, statisticians and domain experts. Our expert panelists with discuss their viewpoints on balancing human-based analysis with automated analytics and machine learning.
newsNew and updated solutions and services from IBM, Tableau, salesforce.com and more
surveyBanks have a great deal of data available, but lack the technology to make the most of it, a Deloitte survey has confirmed. Almost a third of bankers characterize the quality of data in their organization as "adequate"
industry eventHospital Corporation of America is wrapping up the first phase of an initiative to use real-time and near real-time analytics to better understand its clinical data

Customer service optimization (CSO) is a technology-enabled discipline that puts customer service professionals in position to deliver outstanding service. The goal is to correctly resolve each incident without subjecting customers to time-consuming and annoying delays such as waiting “on hold,” having to explain their problem more than once or feeling that they are participating in on-the-job training of customer service agents. At the heart of CSO is the ability to access the best, most relevant and up-to-date information available in the organization. Therefore a robust and powerful search capability is an essential component. Being able to quickly find relevant data on a topic, regardless of where it resides and what form it is in, is often the key to achieving the goal of resolving incidents in a single call or interaction. Learn more in this informative white paper.

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