Interview: Adaptive Computing Brings Big Workflow to the Data Center

Jill King

“Our thought process was that Big Data + a better Workflow = Big Workflow. We coined it as an industry term to denote a faster, more accurate and more cost-effective big data analysis process. It is not a product or trademarked name of Adaptive’s, and we hope it becomes a common term in the industry that is synonymous with a more efficient big data analysis process.”

Jaspersoft and MapR Technologies Announce Integration

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Jaspersoft, the Intelligence Inside applications and business processes, recently announced a partnership with MapR Technologies, Inc., a leader in Hadoop technology for Big Data deployments, whereby Jaspersoft’s business intelligence (BI) offering is now integrated with the MapR Distribution for Apache Hadoop.

Interview: Active Archives for Managing and Storing Big Data

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“Active archives are ideal for organizations that face exponential data growth or regularly manage high-volume unstructured data or digital assets. Target markets include life sciences, media and entertainment, education, research, government, financial services, oil and gas, and telecommunications, as well as general IT organizations requiring online data archive options.”

How MPSTOR Delivers Software Defined Storage Across Multiple Services

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MPSTOR integrates virtualization into the software stack to provide better, more robust infrastructure management. “Orkestra enables automated delivery of “Anything as a Service,” allowing cloud operators to create and deliver cost effective, differentiated services.”

StatAce for Cloud Statistics with R

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StatAce is a start-up in cloud based data science and statistical computing offering an online graphical R environment which allows you to quickly and easily analyze large data. It facilitates collaboration with others, tracks the changes to your R scripts, and can be accessed from any device.

Interview: How Anaplan Delivers Innovation in Real-Time Data Modeling

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“The Anaplan revolution is to provide a big-data engine for business users, removing the need to work with data scientists. The ability to scale your data – 100 billion cells in one model, with 1 billion items in a list – will prove to be the key to proliferation, so long as the data is immediate, useable, consumable via apps, and easy to modify. With Anaplan, business users can build a model with 500 million cells, use it for one hour for a specific purpose, and then throw it away and start on a new one if they want! Ease of use is key. This is the future of enterprise big data.”

Interview: Carpathia Leverages Hadoop and the Cloud to Host Big Data Solutions

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“As a cloud operator and managed hosting provider, we’re seeing demand from a wide range of companies that are interested in leveraging the scalability and efficiency benefits of the cloud to better manage, analyze, and extract value from Big Data.”

Revolution Analytics and AWS Join Forces

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Amazon Web Services (AWS) now offers a hosted version copy of Revolution R Enterprise 7, providing an easy way for individuals and organizations to start and test their big-data-styled analysis projects.

Why Big Data Needs Cloud

Daniel Hardman

“Tackling big data without a cloud-centric worldview is sort of like building a skyscraper without doing a soil study first: you might make some initial progress, but sooner or later you’ll discover that you need to understand and thoroughly adapt an (inadequate) foundation. At a minimum, you’ll experience false starts and thrashing; in many cases, you may never place a capstone.”

How Kiuwan Measures and Analyzes the Quality of Your Code

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“Kiuwan does automatic code review based on static analysis in the cloud. It is SaaS model, as opposed to other software quality solutions based in code analysis that are on-premise and very expensive to implement, Kiuwan is an affordable solution in the cloud. We are the Salesforce.com of software quality.”