Organizations should deploy their analytics operations in the cloud.
That was the straightforward message delivered by Doug Henschen, principal analyst at Constellation Research, and Denise LaForgia, director of product marketing at Qlik, who spoke during a webinar on Sept. 8 hosted by Data Science Central -- a subsidiary of TechTarget -- and sponsored by Qlik.
Analytics deployments in the cloud, Henschen and LaForgia noted, provide speed, agility and security that on-premises deployments are unable to match.
Speed and agility are necessary not only for enterprises to outperform competitors, but also simply to survive amid rapidly changing economic conditions due to the COVID-19 pandemic, while security measures ensure the safety of proprietary information and regulatory compliance.
In fact, because of the speed and agility resulting from analytics deployments in the cloud, there's been a sharp increase in cloud spending during the pandemic, as organizations recognize the benefits of the cloud, according to Synergy Research Group.
In March, the firm reported that spending on cloud infrastructure services increased 35% in 2020 to about $130 billion, while data center hardware and software spending fell 6% to under $90 billion. In 2019, spending on cloud and on-premises infrastructures were nearly even, and on-premises spending far outpaced cloud spending before 2019.
"Now, more than ever, businesses are choosing SaaS for modern analytics," LaForgia said. "A lot of that has to do with the way SaaS analytics can power remote and hybrid work and also encourage collaboration around data. Distributed workforces need immediate, governed access to fully interactive analytics from anywhere on any device, and teams need the ability to collaborate."
Need for speed
Speed, according to Henschen, is the top attraction of the cloud.
The performance of major public clouds, which are updated constantly with the latest technology, exceeds the performance of on-premises infrastructures that have to be internally built and maintained. That performance gives startup enterprises a path toward rapid growth and enables existing organizations to efficiently modernize, Henschen noted.
Doug HenschenPrincipal analyst, Constellation Research
In addition, the cloud frees IT staff from having to spend copious amounts of time maintaining entire systems.
"Speed is absolutely the No. 1 driver to the cloud," he said.
Speed, however, goes beyond compute power and the ways the cloud cuts time off completing analytics tasks. It also includes getting started with analytics and the delivery of new capabilities.
Organizations subscribing to SaaS versions of analytics platforms don't have to wait for cumbersome quarterly platform updates and manually install new features. New capabilities are delivered as soon as they're available and are automatically installed.
"Limitless scalability and elastic cost savings are attractive aspects of the cloud, but speed to innovation and rapid time to market are key drivers to cloud computing," Henschen said.
Likewise, LaForgia noted that speed to innovation, like new augmented analytics capabilities, is a significant benefit of analytics in the cloud.
"From the introduction of natural language understanding to machine learning, augmented analytics is evolving so fast, and SaaS is really the only way to keep up to support rapid adoption by ensuring that updates are available instantly and users have immediate access to them," she said.
That same immediate access applies to the initial implementation of an analytics operation, LaForgia continued.
"Of course, SaaS provides a lower barrier to entry, the ability to get up and running quickly and at lower costs," she said.
Agility and security
Speed, meanwhile, is what results in the agility needed to act and react quickly based on changing conditions.
The combination of the compute power of the cloud that cuts the time to develop and complete analytics projects and the immediate access to the latest capabilities enables agility.
Finally, regarding security, Henschen said early fears about cloud security have abated, as public clouds have been generally demonstrated to be more secure than on-premises deployments.
"Recent history has shown us that data breaches are most often with on-premises deployments that aren't properly secured," he said. "It's also pretty clear that few organizations can meet or surpass the security investments that are being made by the major cloud providers."
Cost overrun and lax security are concerns that have held organizations back from deploying analytics in the cloud in the past.
But with a properly designed infrastructure that ensures payment only for what a user consumes and mounting evidence that major clouds are more secure than on-premises deployments, with the exception of SMBs that may not have the same analytics needs as large enterprises, organizations should deploy their analytics operations to the cloud.
"The center of data gravity is now squarely within -- or it's quickly moving to -- the cloud, and with good reason, so BI and analytics deployment have to be there as well," Henschen said.