Posts Tagged ‘Hadoop’

New Partnership Marries Relational Database Querying, Services With Full Text Search

splice-machine-logo-300pxSingular Hadoop RDBMS provider Splice Machine and LucidWorks have entered into a partnership that enables the former’s customers to access and analyze their unstructured data via LucidWorks Search. Splice Machine customers will license one of the industry’s leading offerings of Apache Lucene/Solr separately, but the companies have proved and certified the integration layer that makes full-text, Google-like search on the relational database platform possible.

lworks“Text searching has really come a long way in recent years with platforms like Lucene/Solr,” says Monte Zweben, CEO and co-founder of Splice Machine. “With this relationship you get the best of both worlds – relational database querying and services with full text search.”

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Blurred Lines: RDBMS Vendors Will Add NoSQL Database Features

forrlogoResearch firm Forrester at the end of September issued its Forrester Wave: NoSQL Key-Value Databases, Q3 2014 report. The report looked at seven enterprise-class vendors in the space: Amazon Web Services, Aerospike, Basho Technologies, Couchbase, DataStax, MapR Technologies, and Oracle.

Noting that the current adoption of NoSQL is at 20 percent and is likely to double by 2017, Forrester principal analyst and report author Noel Yuhanna and his co-authors explain that top use cases for key-value database include social and mobile apps, scale-out apps, Web 2.0, line-of-business apps, big data apps, and operational and analytical apps.

That said, he also notes that the lines between key-value store, document database and graph database NoSQL solutions are blurring, as vendors look to satisfy broader enterprise needs and better appeal to app developers. “Relational database management system vendors, such as Oracle, IBM, Microsoft and SAP, will broaden their current relational database products to include key-value, graph and document features and functionality to deliver more comprehensive data management platforms in the coming years,” the report states.

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Big Data Review: What The Surveys Say

bd2Big Data has been getting its fair share of commentary over the last couple months. Surveys from multiple sources have commented on trends and expectations. The Semantic Web Blog provides some highlights here:

  • From Accenture Anayltics’s new Big Success With Big Data report: There remain some gaps in what constitutes Big Data for respondents to its survey: Just 43 percent, for instance, classify unstructured data as part of the package. That option included open text, video and voice. Those are gaps that could be filled leveraging technologies such as machine learning, speech recognition and natural language understanding, but they won’t be unless executives make these sources a focus of Big Data initiatives to start with.
  • From Teradata’s new survey on Big Data Analytics in the UK, France and Germany: Close to 50 percent of respondents in the latter two countries are using three or more data types (from sources ranging from social media, to video, to web blogs, to call center notes, to audio files and the Internet of Things) in their efforts, compared to just 20 percent in the UK.  A much higher percentage of UK businesses (51 percent) are currently using just a single type of new data, such as video data, compared with France and Germany, where only 21 percent are limiting themselves to one type of new data, it notes. Forty-four percent of execs in Germany and 35 percent in France point social media as the source of the new data. About one-third of respondents in each of those countries are investigating video, as well.

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GraphLab Create Aims To Be The Complete Package For Data Scientists

glabData scientists can add another tool to their toolset today: GraphLab has launched GraphLab Create 1.0, which bundles up everything starting from tools for data cleaning and engineering through to state-of-the-art machine learning and predictive analytics capabilities.

Think of it, company execs say, as the single platform that data scientists or engineers can leverage to unleash their creativity in building new data products, enabling them to write code at scale on their own laptops. The driving concept behind the solution, they say, is to make large-scale machine learning and predictive analytics easy enough that companies won’t have to hire huge teams of data scientists and engineers and build the big hardware infrastructures that lie behind many of today’s Big Data-intensive products. And, the data scientists and engineers that do use it won’t need to be experts at machine-learning algorithms – just experienced enough to write Python code.

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Semantic Web Job: Big Data Architect

TekTree Systems LogoNew York’s Tektree Systems is in need of a Big Data Architect. The job description states, “Hadoop Data Architect with both hands-on Big Data and relational experience and deep knowledge of physical data modeling, data organization and storage technology, experienced with high volumes and able to architect and implement multi-tier solutions using the right technology in each tier, based on fit. Required Skills and Qualifications:

  • Design  and development of data models for a new HDFS Master Data Reservoir and one or more relational or object Current Data environments
  • Design of optimum storage allocation for the data stores in the architecture.
  • Development of data frameworks for code implementation and testing across the program
  • Knowledge and experience with RDF and other Semantic technologies
  • Participation in code reviews to assure that developed and tested code conforms with the design and architecture principles
  • QA and testing of modules/applications/interfaces.
  • End-to-End project experience through to completion and supervise turnover to Operations staff.
  • Preparation of documentation of data architecture, designs and implemented code”.

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Big Data Challenges In Banking And Securities

Photo courtesy: Johan Hansson, https://www.flickr.com/photos/plastanka/

Photo courtesy: Johan Hansson, https://www.flickr.com/photos/plastanka/

A new report from the Securities Technology Analysis Center (STAC), Big Data Cases in Banking and Securities, looks to understand big data challenges specific to banking by studying 16 projects at 10 of the top global investment and retail banks.

According to the report, about half the cases involved e petabyte or more or data. That includes both natural language text and highly structured formats that themselves presented a great deal of variety (such as different departments using the same field for a different purpose or for the same purpose but using a different vocabulary) and therefore a challenge for integration in some cases. The analytic complexity of the workloads studied, the Intel-sponsored report notes, covered everything from basic transformations at the low end to machine learning at the high-end.

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Additional Funding For Elasticsearch To Help Company Complement Its RealTime Search And Analytics Stack

elasticsearchlogoElasticsearch – whose Elasticsearch, Logstash and Kibana products for discovering and extracting insights from structured and unstructured data were discussed earlier this year here – has raised $70 million in Series C financing from New Enterprise Associates (NEA). Benchmark Capital and Index Ventures also participated in the round. That brings the total to $104 million over the past 18 months.

“Nearly all companies, start-ups and Fortune 500 enterprises alike, need to be able to slice and dice rapidly expanding data volumes in real time,” says Steven Schuurman, co-founder and CEO. The funding, Schuurman says, will be applied to enhancing sales, marketing and support personnel and efforts, as well as investing in development to build more complementary products that work with the ELK stack.

“Ultimately, this round of funding will help us get to our goal, faster, of making the ELK stack the de facto platform for businesses to gain actionable insights from their data,” he says.

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Skytree Supports Big Data Analytics in Hadoop With Hortonworks Data Platform

sky

SAN JOSE, CA–(Marketwired – Jun 3, 2014) - Skytree®, the Machine Learning Company®, today announced that its predictive analytics software is now available on Apache Hadoop YARN to deliver agile analytics on Hadoop clusters. Skytree’s flagship product — Skytree Server® — is built to provide high-performance Machine Learning and takes advantage of the multi-workload capabilities enabled by YARN’s increased reliability, scalability and manageability. Read more

Gartner Uncovers Who’s Cool In The Supply Chain

Photo courtesy: Flickr/a loves dc

Photo courtesy: Flickr/a loves dc

Gartner recently released its report dubbed, “Cool Vendors in Supply Chain Services,” which gives kudos to providers that use cloud computing as an enabler or delivery mechanism for capabilities that help enterprises to better manage their supply chains.

On that list of vendors building cloud solutions and leveraging big data and analytics to optimize the supply chain is startup Elementum, which The Semantic Web Blog initially covered here and which envisions the supply chain as a complex graph of connections. As we reported previously, Elementum’s back-end is based on a real-time Java, MongoDB NoSQL document database and flexible schema graph database to store and map the nodes and edges of a supply chain graph. A URI is used for identifying data resources and metadata, and a federated platform query language makes it possible to access multiple types of data using that URI, regardless of what type of database it is stored in. Mobile apps provide end users access to managing transportation networks, respond to supply chain risks, and monitor the health of the supply chain.

Gartner analyst Michael Dominy writes in the report that Elementum earns its cool designation in part for its exploitation of Gartner’s Nexus of Forces, which the research firm describes as the convergence and mutual reinforcement of social, mobility, cloud and information patterns that drive new business scenarios.

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Let Your Enterprise Graph Tell You A Story

entgrafEvery picture tells a story, don’t it? Well, turns out that’s true in the enterprise as much as on our Facebook pages. In this case, the picture is the enterprise graph of the workforce – who interacts with whom, when, in what context. And the story is what the patterns of interactions revealed by the graph may say about employee engagement, influence, and how to better leverage all that to the business’ – and the employees’ — benefit.

When Marie Wallace, IBM analytics strategist, looks at social and collaborative networks and other sources of enterprise communications and channels for business processes, such as CRM systems, “I am interested in the narrative,” she told an audience at the Sentiment Analytics Symposium earlier this month. “There is a lot of information in CRM systems – who met with whom, what industry the client is in, what products were presented. All this is valuable and contributes to the enterprise graph.”

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