According to a new paper from Forrester, advanced analytics is a high priority for most organizations—98 percent of survey respondents rated analytics technologies as at least "somewhat important" to driving business priorities.1 These technologies can take various forms. The survey revealed that areas of interest include Internet of Things (IoT) technologies, predictive analytics, artificial intelligence, and automation software.
It may seem natural to assume that most analytics workloads would run on-premises, due to security and latency concerns. But, according to Forrester's research, while certain databases, workloads and applications are better suited to traditional on-premises infrastructure, many new analytics workloads are moving to the cloud. Companies don't have to choose between private or public; a hybrid cloud strategy can balance and optimize cloud and on-premises infrastructure. Especially with recent advances in business intelligence (BI) and security tools, hybrid cloud becomes an integral component of an effective analytics program.
The Best of Both Worlds
The top three data and analytics infrastructure capabilities that organizations are seeking to improve, Forrester says, are performance, security, and cost. Cloud can deliver all three and is rapidly scalable in a way that traditional on-premises infrastructure is not. On the other hand, keeping critical applications and data on-premises can in some cases make more sense. For example, governance and regulatory requirements may prevent a company from transferring data off-premises.
The ability to intelligently land workloads on the optimal infrastructure, and seamlessly move workloads from private to public clouds and back is the beauty of a holistic hybrid cloud strategy. Over the last several years, the most common objective of analytics decision-makers has been to increase their use of cloud-based big data services.2 Cloud offers scalable resources to handle the ever-increasing amount of data and analytic workloads, and is flexible enough to keep pace with constantly changing business needs.
New Technology Makes Hybrid Cloud Analytics a Reality
Those top three priorities mentioned earlier—performance, security, and cost—are at the heart of innovative Intel® technologies. Intel is developing powerful tools that support the seamless integration between private and public clouds and allow cloud-based analytics applications to access on-premises databases with extremely low latency.
By their nature, advanced analytics applications involve complex, highly parallel matrix math operations. Such applications, like deep-learning algorithms, are impractical if they are not run on high-performing, industry-standard CPUs that support these sorts of operation. Powerful Intel® Xeon® Scalable processors, combined with Intel® Optane™ Solid State Drives (SSDs) and Intel's premium high-speed connectivity products can help improve compute speed, data caching, and data transfer rates. Security features from the silicon to the edge and fast encryption-everywhere capabilities address security concerns. Additionally, new BI tools are being developed that offer robust hybrid functionality and integration capabilities.
The demands on IT infrastructure will continue to expand as more data streams in from IoT devices and other sources. All that data must be stored and analyzed—often in near-real-time. The longer a data scientist has to wait for results, the longer it takes to make decisions based on those results. Fast, plentiful compute, storage, and networking resources provided by a hybrid cloud can make advanced analytics faster and help organizations stay ahead of their digital competitors.
To learn more about how forward-thinking companies are using hybrid cloud to gain higher consistency, better security and more agility than is available from any one public or private cloud alone, read the paper, "Reach Your Analytics Goals with Hybrid Cloud".