Most organizations are looking for viable data science and engineering services. They want to build “pipelines” to gather, integrate and analyze their myriad data sources. For many companies, one of the key deployment options for such a solution is the public cloud.
With the cloud, there is no need to build and invest in a complex IT infrastructure. Another key differentiator for the cloud is speed of deployment. This ability to deliver results quickly makes the cloud ideal for a range of projects, especially proof of concept and pilot projects. In fact, with a swipe of a credit card and a few hours for data transfer (depending on data set size), companies can use cloud-based tools to start answering important business questions right away.
As we know, gaining information quickly is increasingly critical in today’s competitive business environment. Yet a common objection is that customers don’t want their data leaving the premises for safety, security and privacy reasons. That mindset is clear in the 2016 Vormetric Data Threat Report, which found that 85% of senior IT executives were “concerned” or “very concerned” about security in the cloud. However, according to Gartner’s top strategic predictions for 2016 and beyond, “Through 2020, 95% of cloud security failures will be the customer’s fault.”
When cloud solutions are properly designed and implemented as part of a comprehensive architecture, and users follow established protocols, the data is just as secure as with traditional systems. And as far as concerns over data—the crown jewels of the company—leaving the building, well, for many businesses, data regularly leaves the premises. Sometimes regulators prefer data to be housed off-site so they can have on-demand visibility, while backup copies for disaster recovery are kept at an off-site location. The reality is while many companies prefer data to stay on premise, it often does leave the confines of the physical business for various purposes.
Another advantage of the public cloud is that when your workloads and data needs change, the cloud can scale to meet evolving priorities and expanded capacity, while features and services can be quickly deployed for enhanced productivity. Cloud architectures provide a dedicated platform that supports many third-party applications and allows new application development for a variety of workloads.
Just about every application vendor now offers a version for the cloud, including apps focused on data and analytics. With the right cloud solution, organizations can perform large scale processing in a distributed way for analysis. And for those interested in implementing a data lake—a large and easily accessible repository of massive volumes of structured and unstructured data—the cloud provides a springboard to jump start the project.
Granted, plenty of organizations are able to gain value from big data without using the cloud. For others, the cloud provides distinct advantages to help them meet their business goals, and they’ll probably find that public cloud offers much more than they expected.