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Information Fusion in Action: A Demo of Objectivity’s ThingSpan

Information fusion has its foundation in data fusion as used by military and intelligence agencies, generally defined as the use of techniques that combine data from multiples sources and gather that information in order to achieve inferences. This process would be more efficient that if the fusion was achieved by means of a single source.

Depending on the model used, there are several levels of assessment or refinement. As the fusion process goes through these different levels, the information is refined as more value is added. Information fusion can be defined as the process of merging information from disparate sources despite differences in conceptual, contextual and typographical representations, typically combining data from structured, unstructured and semi-structured resources.

The world is full of real world objects (people, places, things) and relationships (knows, likes). Information fusion works with these real world objects and relationships, and in the fusion process discovers new objects and relationships. The best way to represent these is in an object model representation.

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Deciphering the Buzzwords: An Infographic on Information Fusion

As a writer and marketer, I’m no stranger to using catchy buzzwords to succinctly explain an important concept that many people are facing. Despite the fact that buzzwords are used so ubiquitously that they are often added to the Oxford English Dictionary (including emoji, twerk, and cakepop, to name a few), they are not as beloved in the enterprise technology industry as they are among consumers.

The irony behind our love/hate relationship with buzzwords, such as Big Data and IoT, is that everyone throws these labels around, but no one can agree on what they mean.

To dispel some of this confusion, I’m here to discuss a term that Objectivity has been at the forefront for years: Information Fusion.

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Objectivity and Intel: Building the Big Data Backbone for the Industrial IoT

We are at the cusp of the golden age of Fast Data. As more and more organizations deploy massive sensor networks, there is a growing imperative to better leverage increasing volumes of data from sensor networks to provide timely insight and improve business operations. At the same time, a recent McKinsey & Co report on the Internet of Things (“Internet of Things: Mapping the Value Beyond the Hype”) points out that in some industries, less than 1% of data from sensor networks is being utilized in discovering operational insights. This chasm between potential and real value can be bridged through improved streaming analytics tools, data fusion tools, and Hadoop-based enterprise data management systems to allow organizations to pursue new data strategies for creating greater value from IoT Fast Data streams.

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Announcing ThingSpan, Objectivity’s Information Fusion Platform for Big and Fast Data

Objectivity has been a pioneer in the world of Big Data, enabling leading businesses and government organizations to rapidly store, analyze, and find all the relationships and connections within their data from multiple sources, even at enormous scale.

Since our company’s founding more than 20 years ago, our solutions have continually expanded to address the most complex and demanding Big Data challenges—and today, we’re thrilled to announce the newest addition to our product line: ThingSpan, a purpose-built information Fusion platform that simplifies and accelerates an organization’s ability to deploy Industrial Internet of Things (IoT) applications.

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Object…What?

Until the mid-1970s, most systems were built using functional systems. Object-oriented systems were introduced with a flurry of promises in the early ‘80s, many of which actually proved to be true, for once.

More recently, people have been talking about object-based systems, object stores and object-based file systems. In this article, I’d like to clarify the characteristics of each type of technology. Truth in advertising—there’s a lot of overlap, so I’ll try to smooth out the bumps in the ride.

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When planning for Big Data events is its own Big Data problem

As a marketing coordinator at Objectivity, I need to have certain qualities: strategic thinking, creativity, and attention to detail—especially when it comes to event planning.

One of the upcoming events that Objectivity will be attending is Strata + Hadoop World, which takes place Sept. 29 – Oct. 1 in New York City. There are many action items to complete before the event starts, one of which is handling logistics. This process can be time-consuming, deciding which giveaways to order, which marketing materials to ship, and which exhibit setup is best suited for this event.

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