June 19, 2012
Recent surveys have shown that cloud-based, predictive analytics are gaining popularity in enterprise environments. While a number of companies have adopted predictive applications, many more plan to adopt similar strategies in the future. Cloud services are uniquely suited to support these programs, as they offer high availability along with flexible compute and storage capacity. These attributes have led analysts to forecast a growth of cloud services supporting enterprise business intelligence workloads.
James Taylor, CEO of Decision Management Solutions, recently highlighted a survey of industry professionals relying on the SmartData Collective for hosting. The data exhibited positive results from current users of cloud-based predictive applications: 43 percent of respondents said that predictive analytics made an impact in their organization, while 11 percent claimed that transformative change in their company was a result of predictive analytics.
Based on the survey, marketing/customer acquisition and customer retention were viewed as having high potential for cloud-based analytics. Other areas included customer management, sales and cross/upselling. Forbes took note of the phenomenon as well, pointing to a Gartner survey of 1,364 IT managers. 27 percent of respondents reported to using or planning to use Software-as-a-Service applications to assist with business intelligence over the next year. Gartner pointed to cost concerns, lack of available expertise and time to value as the main reasons for interest and adoption of cloud services.
Taylor expanded on the time to value phenomenon in the Forbes article:
Using cloud-based predictive analytic solutions has a much faster time to value than alternatives and this represents a critical advantage for the approach. This rapid time to value is also generating interest in cloud-based solutions for testing, experimentation and development even where deployment will ultimately not be cloud-based.
In one case, a direct sales fitness company used cloud analytics to create buyer and inquiry models. As a result, one campaign generated a 25 percent higher response rate along with a 44 percent higher return on investment. Compared to the company’s previous campaign strategies, cloud-based analytics generated a 174 percent increase in ROI.
Many view cloud services as a viable path to increased revenues, though a number of reservations linger about the technology. In the survey of SmartData Collective users, 65 percent of respondents pointed to data privacy and security as primary concerns. Increased complexity, bandwidth and regulatory issues also contributed to user uncertainty.
While the concerns are valid, Taylor believes early adopters will reap the most benefit from cloud-based analytics. Cloud services have much to offer, and given their flexibility, organizations have the option of methodically testing and migrating their applications.
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.