Daniel Gutierrez reported, “Prelert, the anomaly detection company, today announced the release of an Elasticsearch Connector to help developers quickly and easily deploy its machine learning-based Anomaly Detective® engine on their Elasticsearch ELK (Elasticsearch, Logstash, Kibana) stack. Earlier this year, Prelert released its Engine API enabling developers and power users to leverage its advanced analytics algorithms in their operations monitoring and security architectures. By offering an Elasticsearch Connector, the company further strengthens its commitment to democratizing the use of machine learning technology, providing tools that make it even easier to identify threats and opportunities hidden within massive data sets. Written in Python, the Prelert Elasticsearch Connector source is available on GitHub. This enables developers to apply Prelert’s advanced, machine learning-based analytics to fit the big data needs within their unique environment.”
The article continues with, “Prelert’s Anomaly Detective processes huge volumes of streaming data, automatically learns normal behavior patterns represented by the data and identifies and cross-correlates any anomalies. It routinely processes millions of data points in real-time and identifies performance, security and operational anomalies so they can be acted on before they impact business. The Elasticsearch Connector is the first connector to be officially released by Prelert. Additional connectors to several of the most popular technologies used with big data will be released throughout the coming months.”
Image courtesy Prelert.
IBM Taps Global Network of Innovation Centers to Fuel Linux on Power Systems for Big Data and Cloud Computing
CHICAGO, Aug. 22, 2014 /PRNewswire/ — At the LinuxCon North America conference last week, IBM (NYSE: IBM) announced it is tapping into its global network of over 50 IBM Innovation Centers and IBM Client Centers to help IBM Business Partners, IT professionals, academics, and entrepreneurs develop and deliver new Big Data and cloud computing software applications for clients using Linux on IBM Power Systems servers. Read more
Gil Press of Forbes reports, “Gartner released last week its latest Hype Cycle for Emerging Technologies. Last year, big data reigned supreme, at what Gartner calls the ‘peak of inflated expectations.’ But now big data has moved down the ‘trough of disillusionment’ replaced by the Internet of Things at the top of the hype cycle. In 2012 and in 2013 Gartner’s analysts thought that the Internet of Things had more than 10 years to reach the ‘plateau of productivity’ but this year they give it five to ten years to reach this final stage of maturity. The Internet of Things, says Gartner, ‘is becoming a vibrant part of our, our customers’ and our partners’ business and IT landscape’.” Read more
A recent report from David Loshin states, “As our world becomes more attuned to the generation, and more importantly, the use of massive amounts of data, information technology (IT) professionals are increasingly looking to new technologies to help focus on deriving value from the velocity of data streaming from a wide variety of data sources. The breadth of the internet and its connective capabilities has enabled the evolution of the internet of things (IoT), a dynamic ecosystem that facilitates the exchange of information among a cohort of devices organized to meet specific business needs. It does this through a growing, yet intricate interconnection of uniquely identifiable computing resources, using the internet’s infrastructure and employing internet protocols. Extending beyond the traditional system-to-system networks, these connected devices span the architectural palette, from traditional computing systems, to specialty embedded computer modules, down to tiny micro-sensors with mobile-networking capabilities.”
Loshin added, “In this paper, geared to the needs of the C-suite, we’ll explore the future of predictive analytics by looking at some potential use cases in which multiple data sets from different types of devices contribute to evolving models that provide value and benefits to hierarchies of vested stakeholders. We’ll also introduce the concept of the “insightful fog,” in which storage models and computing demands are distributed among interconnected devices, facilitating business discoveries that influence improved operations and decisions. We’ll then summarize the key aspects of the intelligent systems that would be able to deliver on the promise of this vision.”
The full report, “How IT can blend massive connectivity with cognitive computing to enable insights” is available for download for a fee.
Dan Gillick and Dave Orr recently wrote, “Language understanding systems are largely trained on freely available data, such as the Penn Treebank, perhaps the most widely used linguistic resource ever created. We have previously released lots of linguistic data ourselves, to contribute to the language understanding community as well as encourage further research into these areas. Now, we’re releasing a new dataset, based on another great resource: the New York Times Annotated Corpus, a set of 1.8 million articles spanning 20 years. 600,000 articles in the NYTimes Corpus have hand-written summaries, and more than 1.5 million of them are tagged with people, places, and organizations mentioned in the article. The Times encourages use of the metadata for all kinds of things, and has set up a forum to discuss related research.”
The blog continues with, “We recently used this corpus to study a topic called “entity salience”. To understand salience, consider: how do you know what a news article or a web page is about? Reading comes pretty easily to people — we can quickly identify the places or things or people most central to a piece of text. But how might we teach a machine to perform this same task? This problem is a key step towards being able to read and understand an article. One way to approach the problem is to look for words that appear more often than their ordinary rates.”
Photo credit : Eric Franzon
New York University is looking for a Data Curator in New York, NY. The post states, “The Center for Urban Science and Progress (CUSP) at New York University seeks a Data Curator: an information scientist who will work with faculty, researchers, and students in applied urban science to acquire and organize data related to New York City. CUSP is a dynamic research and academic center that requires a Data Curator to manage data ingest and access workflows, to catalog data using and maintaining controlled vocabularies, and to provide reference and data services to faculty, researchers, and students. The Data Curator will manage the Data Lifecycle from beginning to end to ensure that CUSP data is indexed, curated, and stored within the CUSP Data Warehouse for discovery and access. Strategy must be employed to scale for both data volume and data access growth.” Read more
Mark Albertson of the Examiner recently wrote, “It was an unusual sight to be sure. Standing on a convention center stage together were computer engineers from the four largest search providers in the world (Google, Yahoo, Microsoft Bing, and Yandex). Normally, this group couldn’t even agree on where to go for dinner, but this week in San Jose, California they were united by a common cause: the Semantic Web… At the Semantic Technology and Business Conference is San Jose this week, researchers from around the world gathered to discuss how far they have come and the mountain of work still ahead of them.” Read more
Steve Ranger of ZDnet reports, “A group trying to make it easier for Internet of Things devices and services to work together has won £1.6m in funding from the UK government’s Technology Strategy Board. The group of 40 companies — including BT, ARM, and KPMG — is working on a standard for IoT interoperability called HyperCat. The new funding adds to the £6.4m the government has already spent on the project. The idea behind IoT is that everyday items such as thermostats or plant pots can be networked to create new types of services — at a trivial level, for example, a plant pot could tell a thermostat to turn off the heating because the plants were drying out. However, IoT has great potential to enable smart cities and other forms of automation too.” Read more