Cazena unveiled its Data Science Sandbox as a Service. The service is designed to deliver significantly faster outcomes from data science and analytics programs. Now, data scientists can run a wide range of analytics in a flexible cloud environment without having to build, manage or maintain the underlying technology.
IBM announced IBM Machine Learning, the first cognitive platform for continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast corporate data stores. Even using the most advanced techniques, data scientists – in shortest supply among today’s IT skills* – might spend days or weeks […]
ExtraHop, the leader in real-time IT analytics, today announced ExtraHop Addy, the industry’s first cloud service that applies machine learning to the richest source of IT data—wire data—to provide real-time situational insight for IT teams. ExtraHop Addy is always-on, serving as the eyes and ears for IT and helping them take a proactive, data-driven approach to supporting and securing the digital experience.
Panoply.io, the self optimizing analytics infrastructure company, announced results from its survey at AWS re:Invent end of 2016. 833 attendees shared feedback about data warehouse trends, where 80% of the tools are now cloud-based versus on-premise. 60% of respondents found their data warehouse difficult to manage and too complex. Interestingly, 61% of respondents were currently not using any ETL tool at all, 25% using no business intelligence tools at all.
Nimbix, a leading provider of high performance and cloud supercomputing services, announced its new combined product strategy for enterprise computing, end users and developers. This new strategy will focus on three key capabilities – JARVICE™ Compute for high performance processing, including Machine Learning, AI and HPC workloads; PushToCompute™ for application developers creating and monetizing high performance workflows; and MaterialCompute™, a brand new intuitive user interface, featuring the industry’s largest high performance application marketplace available from a cloud provider.
In this contributed article, technical story teller Ken Strandberg, discusses the feeding of high-performance computing (HPC) and enterprise technical computing clusters with data using Lustre, the open source parallel file system that provides the performance and scalability to meet the demands of workloads on these systems.
Alluxio Releases Data Analytics Solution for Alluxio Enterprise Edition and Dell EMC Elastic Cloud Storage
Alluxio (formerly Tachyon), developers of the world’s first system that unifies data at memory speed, today announced a solution with Alluxio Enterprise Edition (AEE) and Dell EMC’s Elastic Cloud Storage (ECS) for big data workloads. The new solution is designed to help Dell EMC ECS enterprise customers deliver more value from data as they transition their businesses to meet the new demands of a digital economy.
Informatica Fast Tracks Journey to the Cloud with Pay-As-You-Go Pricing for Informatica Cloud Services for Microsoft Azure
Informatica, a leading worldwide provider of data management solutions, announced the availability of hourly pricing for Informatica Cloud® Services for Microsoft Azure in the Azure Marketplace. Now available as a pay-as-you-go hourly pricing model, this solution is designed to help users of the Azure cloud platform and Microsoft Cortana Intelligence Suite jump-start cloud data integration and management projects.
In this special guest feature, Gerard Scheitlin, Vice President of Security, Risk, and Assurance at Orion Health, makes the case that big healthcare players are storing big data in the cloud because the benefits of cloud infrastructures are significant and hard to ignore.
This is the second article in a series focusing on a technology that is rising in importance to enterprise use of big data – IoT Analytics, or the analytical component of the Internet-of-Things. In this segment, we’ll discuss the marriage of IoT analytics and the cloud. The cloud is enabling innovation and driving the adoption of many new and powerful technologies, and IoT is no exception. One characteristic of many IoT applications is they generate “too much data.” You don’t necessarily know the value of that data and the process tends to be very elastic.