Over the next five years, we will see a mind-blowing explosion of data. Try to wrap your head around this: 1.7 megabytes of new information will be created every second for every human, adding up to 44 zettabytes of data (IDC). To garner any value from all this Big Data, we have to process it. How will our storage and compute infrastructure keep up?

Many of today’s complex science, engineering, development, and business problems require high performance compute (HPC) capabilities. Everything from particle physics to smart cities depends on processing power and speed that break new ground. Big Data is key to both identifying the right questions and coming up with the best answers, and in many use cases the compelling value lies in coming up with those answers in real time.

Power up in the cloud

Researchers and innovators have begun seeking access to a mix of infrastructure and applications that will generate the Big Compute power they need. On-premise infrastructure continues to be too expensive and complex for many organizations that need next level data and analytics capabilities.

As cloud infrastructure technology and integrated service delivery matures and goes mainstream, confidence in the security and reliability of public and hybrid cloud infrastructure deepens, opening new frontiers. The HPC capabilities required for certain projects are becoming available through “as-a-service” models, enabling enterprises and researchers to access the right level of computing and low-latency service for their specific needs.

The potential applications of Big Data and advanced analytics powered by HPC in the cloud are electrifying. Consider what you could learn about customer marketing, supply chains, or manufacturing operations by truly leveraging the entire body of data your organization has collected. Business intelligence will be profoundly enriched—not to mention the ability to model and test complex engineering and scientific problems.

Form a data strategy

Not every Big Data project requires HPC capabilities. Many organizations are still trying to wrangle their valuable data collections into an accessible system. One size cloud does not fit all—when forming a modern data strategy, it’s important to assess storage and compute needs, latency requirements, and business objectives in order to deploy the right mix of on-premise and cloud options, including as-as-service offerings for infrastructure, platform, and software needs.

Advanced challenges emerge alongside advanced capabilities when we move into implementation and practical use: the security of systems and data; compliance requirements; and global market pressures including disruptive competition, skills shortages, and economic uncertainty. As a result, the majority of enterprises have just begun to leverage their data into valuable insights.

Ramp up to the next level

Companies are under intense pressure to ramp up to Big Data competency. The statistics in a recent Forbes forecast highlight the rapid rise of analytics. The global market for Big Data and business analytics software will grow 50 percent to $187B by 2019. The market for prescriptive analytics software alone will grow at 22 percent CAGR to $1.1B in 2019. In less than 5 years, 40 percent of net new business intelligence investments will be funneled into predictive and prescriptive analytics.

These near term forecasts are a clear argument for figuring out how to harness the power of analytics before your competitors do. The good news is, all that untapped data promises limitless opportunities once we apply the power of Big Compute. Case in point: CERN scientists are using HPC in the cloud in their quest to figure out how the universe works—literally.

HPC in the cloud can boost an enterprise’s ability to figure out their “universe” by, for example, analyzing thousands of concurrent transactions in real time to spot trends and opportunities. High speed processing of terabytes of data is required for projects where data sets are dynamic or insights are generated and applied in real time. Commodity compute won’t suffice for the complex algorithms that underpin transformative technologies like machine learning, predictive and prescriptive capabilities, and complex modeling tools.

Big Benefits

Big Data analytics help companies optimize products, service delivery, and operations. Predictive and prescriptive analytics are advancing fraud detection, APT pattern detection, scenario modeling, and behavioral profiling for HR use. Growing technology paradigms like IoT, bioinformatics, and robotics and automation are certain to push infrastructure innovation to pioneering levels of capacity and performance.

HPC in the cloud represents one of the biggest transformations in computing since the PC, with the potential to advance digital business and research exponentially, even going beyond Moore’s Law. What may seem like science fiction to the general public—deep learning, neural networks, artificial intelligence—is actually happening now, fueled by data experimentation and analysis platforms running on powerful GPU and FPGA systems in the cloud.

It’s time to get on board now and prepare a next generation Big Data strategy. Those with big compute capabilities in place will be ready to chart a course, full speed ahead. Those who missed the boat will drown in a sea of data.

Leo Reiter is CTO at Nimbix, a company that offers cloud-based HPC infrastructure and applications.