Advanced Computing in the Age of AI|Monday, February 24, 2020
  • Subscribe to EnterpriseAI Weekly Updates:  Subscribe by email

Big Data ‘Center of Gravity’ Shifting to Cloud 

As practitioners of big data analytics seek to bring computing power closer to the data rather than the other way around, the cloud is emerging as the preferred platform for increasingly sophisticated data crunching by more industries adopting big data strategies.

For now, market watcher Wikibon concluded in a big data vendor and market forecast released this week that cloud services represent only a fraction of a big data market expected to top $35 billion this year. Last year, for example, the market survey found that cloud services accounted for about $1.3 billion of a booming $27.3 billion big data market. By contrast, the "professional services" sector delivering analytic tools represented more than $10.4 billion in big data revenues.

But those trends are said to be reversing as more enterprises move to the cloud and the adoption of big data tools moves up the corporate ladder from IT operators and data scientists to the corner office.

Wikibon reported that big data-related cloud services, including infrastructure-, platform- and software-as-a-service offerings, are "still in the early stages of development" as part of big data deployments, accounting for only 5 percent of the overall big data market.

"The vast majority of Big Data production workloads today are hosted on-premises, as by and large that is where the data being processed and analyzed 'lives'," the market research added.

For now, most big data production workloads are hosted on-premises, but Wikibon foresees the big data "center of gravity" shifting to the cloud as more enterprises deploy cloud infrastructure or embrace hybrid cloud options as a way to leverage cloud technology while securing sensitive or proprietary in-house.

"Big data is heavy, and a central tenet of big data is to bring the compute to the data rather than the data to the compute," the survey stressed. "The cloud offers the added benefit of abstracting away significant layers of complexity associated with internally-hosted big data deployments."

Hence, Wikibon sees big data deployments fueling the adoption of cloud infrastructure that will be increasingly easier to deploy. As the cloud becomes the preferred host for big data deployments, Wikibon forecasts that cloud vendors will take a big chunk of revenue away from professional services providers like IBM, Accenture, Deloitte and Capgemini who currently dominate the provisioning of big data analytics.

Indeed, it is increasingly common to hear cloud vendors laying plans to integrate data analytics into their offerings. That approach is widely seen as the best way to move computing power closer to huge volumes of structured and, with the rise of mobile and other connected devices, unstructured data—much of it with a very short shelf life.

Along with IBM, early proponents of cloud-based big data deployments include vendors like Cloudera, the enterprise data hub specialist that is also actively courting the emerging federal cloud market.

Other likely beneficiaries of big data's transition to the cloud are major public cloud vendors like Amazon Web Services, Google Cloud Platform and Microsoft Azure. According to the Wikibon survey, Microsoft racked up an estimated $532 million in big data revenues in 2014, placing the cloud vendor among the top 10 big data vendors. Amazon's 2014 big data revenues totaled about $440 million while Google reached an estimated $225 million last year, the market analyst said.

Overall, Wikibon forecasts the "cloud services" related to big data deployments could reach $5.69 billion by 2020.

 

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).

Add a Comment

Do NOT follow this link or you will be banned from the site!
Share This