“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.”
“Deep storage, and tape library-based storage in general, benefit organizations that are looking to incorporate low-cost, high-density, scalable storage into their fast-growth data environments. Industries that recognize the value and regularly rely on tape storage include education, federal and state government, finance, life sciences, media and entertainment, oil and gas exploration, and Web 2.0, among others.”
“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.”
“A Big Workflow approach to big data not only delivers business intelligence more rapidly, accurately and cost effectively, but also provides a distinct competitive advantage. We are confident that Big Workflow will enable enterprises across all industries to leverage big data that inspires game-changing, data-driven decisions.”
OneFold believes that the expertise of a data scientist should be used for solving the most complex of analysis and not for the more day-to-day aspects of data extraction. The company uses a plug and play DHQL platform for automated data extraction, transformation, querying and reporting. Navneet Aron and Uday Sandhar, co-founders of OneFold, teamed up to answer our questions about this intriguing technology.
“SAS In-Memory Statistics for Hadoop software enables multiple users to concurrently manage and prepare data stored in Hadoop, explore and visualize this data, develop accurate statistical and machine learning models quickly, as well as access, deploy and execute these models in their Hadoop ecosystem.”