Enterprise Data

Pitney Bowes Chooses Neo4j to Power Its Spectrum MDM Product Line

neoSAN MATEO, CA, Dec 16, 2014 (Marketwired via COMTEX) — Neo Technology, creators of Neo4j, the world’s leading graph database, today announced that Pitney Bowes Inc. a provider of technology solutions for small, mid-size and large firms that help them connect with customers to build loyalty and grow revenue, is successfully using Neo4j to build and maintain a comprehensive knowledge graph of critical information across data and application silos as part of its Spectrum Master Data Management (MDM) offering. Read more

Big Data, the Semantic Web, and Enterprise Content Management

ecmAnand Srinivasan of Smart Data Collective recently wrote, “There has been talk about the arrival of Web 3.0 –the semantic web – for quite some time now. There is already a lot of progress here with the implementation of things like the RDF schema and the semantic web stacks. The approach so far has been top-down with standardization tools introduced and webmasters being asked to implement them on their websites. However, a truly semantic web may not be possible unless there is a desperate need for businesses to implement them on their websites. And that, in my opinion, is going to come from the evolution of the enterprise content management (ECM) industry. ECM, for the uninitiated, comprises of the technologies, methods and tools that are used by businesses to organize and store their organization’s documents.” Read more

Tamr On Mission To Curate And Connect Data

tamrlogoMake it as easy to add and connect new data sources into the enterprise analytics infrastructure as it is to add a new web site onto the modern web. That’s where next-gen data curation company Tamr, a startup born from an MIT research project to bring together lots of tabular data sources in a scalable and repeatable way.

Just like Google does all the work to find and connect web sites hosting the information that users want, “we want to do the same with tabular data sources inside the enterprise,” says Tamr co-founder and CEO Andy Palmer. “Tamr provides systems of reference. If you are looking for attributes to add to an analysis or want data to support something, you have this reference place to go in the enterprise with a catalogue of all the data that exists across the company.”

So often businesses want to use analytics to address hard questions, but can’t do so successfully unless they are integrating lots of disparate data sources and creating a referential catalog. With Tamr, Palmer says, they can ingest data sources very quickly into a semantic triple store, make them available in real time, and connect them using machine learning to map attributes and match records, in support of providing a unified view of a given entity that can then be consumed by various business intelligence and analytics tools. To be useable, he points out, data has to be “very, very thoroughly connected into everything else for there to be context and reference for how it can be consumed and whether it is reliable.”

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Expert System Extends the Cogito API Portfolio

Expert System LogoPALO ALTO, CA–(Marketwired – Nov. 17, 2014) – Expert System (EXSY), the leader in semantic technology, announced today the availability of the Cogito API. As a fully configured API series, Cogito API transforms a business’ ability to organize, link, find and understand unstructured information within corporate intelligence, CRM, human resources, data management, knowledge management and social media monitoring applications.

Using Cogito API, the topics, concepts, entities, relationships and sentiment expressed in any massive collection of text can be analyzed and understood; the data output is returned in a UTF-8 JSON or XML format and made instantly ready to use in enterprise solutions ranging from customer care, sentiment analysis and advanced business intelligence. Read more

Data Innovation, Driven By Semantic Models, Machine Learning And More

VRThe Ventana Research summit took place this week, and semantic and related technologies had a place at the table.

Among the keynoters discussing the topic of Inspiring Business Technology Innovation to Change Business and IT Forever, for example, was Nedshad Bardoliwalla, co-founder and vp of products at data prep vendor Paxata. He discussed the need to rethink how to innovate with data, as that will “drive the biggest increases in value for your organization for the foreseeable future.”

As part of that, he explained that in a world where everything physical on the planet will have a digital representation, businesses should pay attention to factors including the “massive and interesting algorithms around recognition systems, around deep learning, around semantic models that let us understand images and text in ways we never could….Take advantage of those if you are to innovate and bring capabilities to market that change way people think of data.”

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Unearthing Data on Non-Public Companies with Artificial Intelligence

datafoxGreg MacSweeney of Wall Street and Tech recently wrote, “It’s relatively easy to find information on public companies. Bloomberg, Thomson Reuters, and Dun & Bradstreet, for example, all have in-depth information that is accessible to anyone with a subscription. But where do investment bankers, venture capitalists, and other investors find reliable information about private companies? If you talk to investment bankers, or other investors who are looking for information on non-public companies, it quickly becomes apparent there is no easy answer. Investment bankers rely mostly on Google searches and a combination of information gathered from Hoovers, S&P Capital IQ, Dun & Bradstreet, and others. But it is a laborious manual process to do due diligence on private companies.” Read more

TopBraid Suite 4.5 Puts The Focus on Enterprise-User Readiness

tqSemantic data integration vendor TopQuadrant’s TopBraid Suite 4.5 just hit the street, a major release that CMO and VP of Professional Services Robert Coyne says “provides a large number of new and enhanced capabilities driven primarily by customers who are using our TopBraid Enterprise Vocabulary Net solution for vocabulary and/or metadata management, or using TopBraid Live to create a custom, model-driven solution.”

The latest version, he says, features more business user and enterprise readiness-motivated improvements than any past major release since Release 4.0, when the current generation of the TopBraid EVN product was first introduced. Many of the enhancements were inspired by requests coming from different customers using TopBraid in different contexts, he notes.

New capabilities in EVN range from improved configurability for the EVN Ontology Editor, via a form builder that allows browser window management and enables users to open multiple view forms, tree and chart windows, to an improved search form that makes it possible to search on cardinalities, regular expressions, aggregates in the search counts and chart results.

Also part of the upgrade is increased support for business stakeholders who need to collaborate on defining and linking enterprise vocabularies, taxonomies and metadata used for information sharing, data integration and search. Features like that reflect the fact that a growing number of enterprise customers and business users are looking to leverage products such as TopBraid EVN, Coyne says.

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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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Data-Intensive Businesses Turn to Infobright to Transform Machine-Generated Data into Business Improvements

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TORONTO–(BUSINESS WIRE)–Infobright, the database analytics platform for the Internet of Things (IoT), today announced that Rez-1Smart 421, and PayPoint, three data-heavy businesses in the financial services, logistics and transportation industries, selected Infobright’s Enterprise Edition to transform their machine-generated data into business insights. The Infobright analytic database platform enables customers to interrogate machine and IoT generated data to quickly identify the patterns that drive smarter business decisions. Read more

Smarter Enterprise Data with Machine Learning and Cognitive Computing

Watson

Jorge Garcia of Wired recently wrote, “IBM’s recent announcements of three new services based in Watson technology make it clear that there is pressure in the enterprise software space to incorporate new technologies, both in hardware and software, in order to keep pace with modern business. It seems we are approaching another turning point in technology where many concepts that were previously limited to academic research or very narrow industry niches are now being considered for mainstream enterprise software applications. Machine learning, along with many other disciplines within the field of artificial intelligence and cognitive systems, is gaining popularity, and it may in the not so distant future have a colossal impact on the software industry. This first part of my series on machine learning explores some basic concepts of the discipline and its potential for transforming the business intelligence and analytics space.” Read more

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