As enterprises are grappling with exponentially growing big data, they are striving to leverage the potential of cloud technologies. A growing number of organizations are building agile and efficient cloud environments to maintain clusters of servers in order to effectively support tools processing large volumes of high velocity big data formats.

Cloud computing business models are deployed on a range of servers, networking, and online data storage resources. It is a cost effective way of supporting advanced analytical applications, which can be easily scaled up/down, as required, to drive business value.

Let’s dig deeper to understand this framework in detail:

Initial interests in the big data methodology primarily focused on social and business information sources like corporate emails, Facebook & twitter posts, videos, and other online activities. As the scope of this field started growing, techno gurus began to include content from intelligent systems like kiosks, in vehicle infotainment, device sensors, and smart meters located at the edge of networks. This facilitated large volume of highly complex and fast streaming data that required to be synthesized appropriately to gain fast, accurate, and richer business insights without incurring high capital expenditures.

In this light, service provider offering cloud hosting solutions turned out to be a reality for enterprises of all shapes and sizes. Private cloud deployment model is leading in this regard. Moreover, as clouds are maturing, they are able to effectively address the security barriers in a better way to support swift delivery of this cutting edge technology while demonstrating stronger trust in the computing models. A survey conducted by Ubuntu in the year 2013 revealed that approximately 55% of the companies are consider to migrate to the cloud to store and operate their mission critical workloads in a secured environment.

Capitalizing on cloud infrastructure for analyzing multiplying data and information makes sense as cloud-enabled delivery models are known for offering exceptional elasticity that enables an organization’s IT team to formulate the best possible approach, which is custom-built in line with their changing business needs. For instance, enterprises supporting internal private clouds can easily add huge data analytics in their inhouse offerings by either availing services from a reliable services provider or can alternatively build its own hybrid cloud infrastructure capable of protecting sensitive information and applications in the cloud while leveraging external information sources in the public cloud.

Hence, companies are tapping on the potential of cloud models to power their business with the scalable analytical solutions. Cloud technology offers efficiencies and flexibility for delivering business insights, accessing information, and driving their business value.