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Syapse Selects SYSTAP’s Bigdata® as Semantic Database for Precision Medicine Data Platform

Syapse and BigData logosFor immediate release: 8/19/2014

WASHINGTON, D.C. – SYSTAP, LLC. today announced that Syapse, the leading provider of software for enabling precision medicine, has selected Bigdata® as its backend semantic database. Syapse, which launched the Precision Medicine Data Platform in 2011, will use the Bigdata® database as a key element of their semantic platform. The Syapse Precision Medicine Data Platform integrates medical data, omics data, and biomedical knowledge for use in the clinic. Syapse software is delivered as a cloud-based SaaS, enabling access from anywhere with an internet connection, regular software updates and new features, and online collaboration and delivery of results, with minimal IT resources required. Syapse applications comply with HIPAA/HITECH, and data in the Syapse platform are protected according to industry standards.

Syapse’s Precision Medicine Data Platform features a semantic layer that provides powerful data modeling, query, and integration functionality. According to Syapse CTO and Co-Founder, Tony Loeser, Ph.D., “We have adopted SYSTAP’s graph database, Bigdata®, as our RDF store. Bigdata’s exceptional scalability, query performance, and high-availability architecture make it an enterprise-class foundation for our semantic technology stack.”

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A Look At The State of Information Governance

igiThis month saw the release of the Information Governance Initiative’s Annual Report for 2014, a study aiming to report the perceptions of information governance practitioners, providers and analysts as well as advance information governance as a concept, market and operational model.

The IGI consortium and think tank was founded by leaders in the information governance field and supported by vendors with semantic tech and text analytics backgrounds, including EquivioHP/Autonomy, OpenText, Recommind  and Zylab. About 500 respondents provided input to the survey.

About 80 percent of these respondents agreed that IG included risk- and value-focused activities, with the focus, however, on risk prevention, with efforts such as records information and management, information security and compliance as the top-marked concepts. That said, more than 50 percent of respondents in each case include among IG’s facets big data, business intelligence, and data science – and IGI believes that the value side will continue to grow, given the significant recent advancements in data analytics and their continuing spread through the enterprise. Given how far IG’s facets extend, “IG should serve as the coordinating function for all of these activities, tying them together into one humming, efficiently functioning operation.”

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EverString Raises $12M to Bring Machine Learning to Clients

logo-esJonathan Vanian of GigaOM reports, “EverString, a big data startup that helps companies identify prospective sales leads and new clients though predictive analytics, has raised $12 million in a series A funding round. Lightspeed Venture Partners led the round, which also included existing investors Sequoia Capital and IDG Ventures. While there are a host of marketing analytics services in the market like Silverpop and Eloqua that businesses use to aggregate numerous sales leads and find potential customers, EverString’s technology goes beyond whatever data is hosted internally within a company and branches out to the open web, explained EverString’s co-founder and CEO, Vincent Yang.” Read more

Google Acquires Emu, a Messaging & Personal Assistant App

emuMark Langshaw of Digital Spy reports, “Google has acquired the company behind Emu, a messaging app that doubles as a personal assistant. The existing application, which was for iPhone only, will be pulled from the App Store later this month.’As of August 25, 2014, we’ll be shutting down the Emu app. It will no longer be available in the App Store, and existing users won’t be able to send, receive, or download messages. We know it’s an inconvenience, and we regret that,’ said the firm in a statement. Emu uses intelligent learning and natural language processing to present the user with relevant information in real-time, and can be integrated with other services.” Read more

Startup Adatao Raises $13M to Bring Search to Big Data

adataoDeborah Gage of The Wall Street Journal reports, “Making big data stores as easy to search as Internet data has been a holy grail for the software industry, and it’s become a more pressing problem since the growth of the big data software Hadoop, which holds enormous amounts of data. Adatao Inc., a startup based in Sunnyvale, Calif., has raised nearly $13 million in Series A funding led by Andreessen Horowitz to take on the challenge. Founded in 2012 by veterans of Google Inc., Yahoo Inc. and the Army Research Lab, the company combines machine learning, natural language processing and in-memory (i.e. fast) computing to create a system in which users can write queries in ordinary English or one of several computer languages-—Smart Query, SQL, Scala, Java, Python or R–and get results in less time than it takes to speak their questions.” Read more

Big Data Holds Great Power, But Only if You Know How to Mine It

27498728_b84f8817aaChloe Green of Information Age recently wrote, “Handling immense data sets requires a combination of scientific and technological skills to determine how data is stored, searched and accessed. In science, the importance of data scientists in ensuring that data is handled correctly from the outset is not underestimated; other industries can learn from the scientific approach. Text-mining tools and the use of relevant taxonomies are essential. If we think about big data as a huge number of data points in some multi-dimensional space, the problem is one of analysis, i.e. frequently finding very similar or very dissimilar points which cannot be compared. In life sciences, taxonomies assign data points a class, thus comparison of two points is as easy as looking up other data points in the same class.” Read more

How Natural Language Processing and Big Data are Making Sense of Consumer Behavior

ATTENSITY LOGODana Gardner of CRM Buyer recently wrote, “The power of Big Data technology is being successfully applied to understanding such complex unknowns as consumer sentiment and even intent. That understanding then vastly improves how retailers and myriad service providers manage their users’ experiences — increasingly in real time. Fortunately, today’s consumers are quite willing to share their intents and sentiments via social media, if you can gather and process the information. Hence the rapidly developing field of social customer relationship management, or Social CRM.” Read more

Deep Learning Startup Madbits Acquired by Twitter

MADBITSDerrick Harris of GigaOM reports, “Twitter has acquired a stealthy computer vision startup called Madbits, which was founded by former New York University researchers. Clément Farabet and Louis-Alexandre Etezad-Heydari. Farabet is a protégé of Facebook AI Lab director and New York University professor Yann LeCun, while Etezad-Heydari was advised by Larry Maloney and Eero Simoncelli.” Read more

Improving Customer Security with Machine Learning

2294144289_a54db90ac5_nRick Delgado recently wrote on Mike2.0, “When you get right down to it, computer security is all about being able to analyze the data. A company’s security is largely dependent on the amount of data analysis they’re capable of, along with the quality of that data. A company that can collect a lot of data at once but doesn’t have the means to analyze it properly for threats won’t get very far. The same goes for a business with excellent analytic tools but without the resources to gather and store that information. These facts are very important because without a lot of data, machine learning simply can’t be as effective.” Read more

How GS1 is Shaping eCommerce in the Semantic Web

gs1Andrew Osborne, CTO of GS1 UK recently shared an overview of how the non-profit is leveraging the Semantic Web to improve customer experiences. He writes, “For those of you unfamiliar with what GS1 actually does, we are a not-for-profit standards development organisation. Put simply, our role is to define data structures and how these are used to identify things, a role we have been performing since the 1970s. We provide a series of ‘keys’ for industry which identify various types of entity (products, locations, assets and so on) and which have highly developed allocation rules. We have also defined product attributes for bar coding (the application identifier standards), have over 1,000 product attributes defined for synchronisation in the Global Data Synchronisation Network and an extensive Global Product Classification that is used to categorise products. For visibility systems we have a standard ‘Core Business Vocabulary.’ “ Read more

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