Sangeeta May 11, 2014 No Comments
A convergence of data and cloud computing
Data analytics using cloud computing or cloud services have led to the evolution of cloud analytics, where the flexible infrastructure of cloud models facilitate data analytics in collaboration with the cloud service provider.
Why analytics in the cloud?
Organisations rely upon legacy systems for data warehousing. These cannot always manage the explosive growth of data or convert it into useful information and insight. This gap has paved the way to exploring the cloud’s many models and capabilities for solving problems and adopting solutions for analytics. The end-user is able to see the key performance indicators (KPIs) and retrieve useful information on a daily basis.
As cloud services are increasingly embedding analytic engines into their solutions and service delivery mechanisms, enterprises of all sizes are adopting the cloud for their solutions. With a wide choice of public or private cloud service models, free-to-use cloud service, pay-as-you-go or subscription based pricing, it is possible to leverage these services for advantages of data storage, applications and resources.
So how do you define cloud analytics?
My favourite definition from Techopedia – what is cloud anlytics:
Cloud analytics is primarily a cloud-enabled solution that allows an organization or individual to perform business analysis or intelligence procedures. These solutions and services are delivered through cloud models, such as hosted data warehouses, SaaS business intelligence (BI) and social media analytic products powered by the cloud. Cloud analytics services work like a typical data analytics service, providing similar features and capabilities. The only difference is that cloud analytics integrates some or all of the service models of cloud computing in delivering that solution. (Techopedia)
According to Gartner’s,
“cloud analytics refers to any analytics effort in which one or more of these elements is implemented in the cloud, be it public or privately owned.” The six elements are data sources, data models, processing applications, computing power, analytic models, and sharing or storing of results”.
“a set of technological and analytical tools and techniques specifically designed to help clients extract information from massive data. It leverages the use of Cloud and related computing, communications, and data management and visualization technologies to quickly and more economically perform sophisticated multivariate analysis on massive centralized, distributed, and/or federated data sets to better understand and help solve complex problems”.
Popular Cloud Analytics products:
Key Industry verticals using Cloud Analytics: banking, financial services and insurance (BFSI), consumer goods and retail, telecommunications, healthcare & life sciences, media & entertainment, government , business & consulting services, research & education, energy and manufacturing.
Key Global Statistics:
The bottom-line is that Cloud Analytics helps organisations gain valuable insights from large data sets, and use the knowledge to gain business advantage at affordable costs.