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Big Data Analytics and Sense Making with Synthesys

Tim Estes is the CEO and co-founder of Digital Reasoning. Digital Reasoning develops and markets solutions that provide Automated Understanding for Big Data.

There’s a great deal of talk about “big data” today. If you walk into an AT&T store near you, you may see the statistics of users sending over 3 Billion text messages a day or over 250 million tweets. Compare that to closer to 100 million or less tweets a day a year or two ago, and it’s daunting how rapidly the volume of digital information is increasing. A mobile phone without expandable storage frustrates users who want to keep a contacts list, rich media, and apps in their pocket. In organizations, the appetite for storage is significant. EMC, Hewlett Packard, and IBM are experiencing strong demand for their storage systems. Cloud vendors such as Amazon and Rackspace are also experiencing strong demand from companies offering compelling services to end users on their infrastructure. At a recent Amazon conference in Washington, Werner Vogels revealed that the AWS Cloud has hundreds of thousands of companies/customers running on it as some level. Finally, companies like Digital Reasoning are working the next generation of Cloud – automated understanding – that goes from a focus on infrastructure to sense-making of data that sits in hosted or private clouds.

While most of the attention has been on infrastructure like virtualization / hypervisors, Hadoop, and NoSQL data storage systems, we think those are really the enablers of the killer app for Cloud- which is making sense of data to solve information overload. Without next generation analytics and supporting technology, it is essentially impossible to:

• Analyze a flow of data from multiple sensors deployed in a factory
• Process mobile traffic at a telephone company
• Make sense of unstructured and structured information flowing through an email system
• Identify key entities and their importance in a stream of financial news and transaction data.

These are the real world problems that have engaged me for many years. I founded Digital Reasoning to automatically make sense of data because I believed that someday all software would learn and that would unleash the next great revolution in the Information Age. The demand for this revolution is inevitable because while data has increased exponentially, human attention has been essentially static in comparison. Technology to create better return on attention would go from “nice to have” to utterly essential. And now, that moment is here.

Digging a little deeper, Digital Reasoning has created a way to take human communication and use algorithms to make sense of it without having to depend on a human design, an ontology, or some other structure. Our system looks at patterns and the way a word is used in its context and bootstraps the understanding much like a human child does – creating associations and building into more complex relationships.

In 2009, we migrated onto Hadoop and began taking on the problem of managing very large scale unstructured data and move the industry beyond counting things that are well structured and toward being able to figure out exactly what the data means that you are measuring.

Digital Reasoning asks the question: “How do you take loose, noisy information that is disconnected and unstructured and then make sense of it so that you can then apply analytics to it in a way that is valuable to business?”

We identify actors, actions, patterns, and facts and then put it into the context of space and time in an efficient and scalable way. In the government scenario, that can mean to finding and stopping bad guys. In the legal environment they want to answer the questions of “who”, “what”, “where”, and “when”.

Digital Reasoning initially set our focus on the complex task of making sense out of massive volumes of unstructured text within the US Government Intelligence Community after the events of 9/11. But we also believe that our Synthesys software can be utilized in the commercial sector to create great value from the mountains of unstructured data that sit in the Enterprise and streaming in from the Web.

Companies with large-scale data will see value in investing in our technology because they cannot hire 100,000 people to go through and read all of the available material. This matters if you are a bank and trying to make financial trades. This matters for companies doing electronic discovery. This matters for health sectors that need help organizing medical records and guarding against fraud.

We are an emerging firm, growing rapidly and looking to have the best and the brightest join our quest to empower users and customers to make sense of their data through revolutionary software. With the recent investment from In-Q-Tel and partners of Silver Lake, I believe that Digital Reasoning has a great future ahead. We are on the bleeding edge of what is going on with Hadoop and Big Data in the engineering area and how to make sense of data through some of the most advanced learning algorithms in the world. Most of all we care that people are empowered with technology so that they can recover value and time in the race to overcome information overload.

To learn more about Digital Reasoning, navigate to our Web site and download our white paper.

Tim Estes, December 19, 2011

Sponsored by Pandia.com

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