b-eye-network.com has come up with a neat article on “What’s Up with Cloud Analytics?” and we have compiled a shorter blurp on the same.

Cloud computing is the popular and widely used term for virtualization of computing services. Cloud technology is all about services, and it fits into several categories:

• Software as a Service (SaaS) is an Internet-based model for deployment of software applications. SaaS allows on-demand use of applications without the need to license and install for every computer where the software is used. SaaS is differentiated from earlier client-server and application service provider (ASP) models by multi-tenant architecture where many customers simultaneously use a single instance of the software.
• Data as a Service (DaaS) is a relatively recent term that encompasses four somewhat different kinds of service models.
  • Most common among DaaS models is the “data marketplace” where many different kinds of data are available on a pay-per-use basis. Marketplace data can be combined with internal data to enrich data warehouses and add new dimensions to analytics.
  • Some providers of data marketplace services extend the model to include some data quality, standardization and correlation services. Most of these services revolve around address data and go beyond common address standardization routines to include features such as delivery route optimization.
  • A more recent and emerging DaaS model uses web services to create a developer-centric data hub. In this model, developers upload their own data to be hosted by the DaaS service provider. Developers can then build web services around that data.
  • Finally, the acronym DaaS is also used to mean data warehousing as a service, an architecture in which data and BI applications are hosted in a virtualized environment and deployed using a services model.
    
    
• Platform as a Service (PaaS) is an approach to virtualizing the hardware, operating systems, applications frameworks and technology stacks upon which applications are built and deployed. PaaS removes the cost and complexity of buying and managing the hardware and software layers needed to deploy applications. A PaaS environment supports the entire life cycle of building, delivering, operating and supporting web applications.
  
  
• Infrastructure as a Service (IaaS) is an architecture of virtualized hardware and operating systems. On the surface it sounds a lot like another name for PaaS, but there are some subtle differences. PaaS provides developer environment as well as operations environment but is limited to web applications. IaaS delivers only the operations environment but supports a broader range of applications. IaaS is, in fact, the foundation upon which PaaS environments are constructed.
  
  
• Analytics as a Service has not been tagged with the acronym AaaS, perhaps due to the inevitable vocalization that is sure to fail as a marketing buzzword. But analytics as a service is a concept that is gaining attention in the BI community. Analytic services are built upon SaaS and DaaS foundations to create analytic applications and OLAP engines as web-hosted and web-deployed applications.

Today the Cloud Services are very real and available. The BI solutions on the cloud are also being made available to people, business and enterprises. But when would the transfer complete to the cloud,  is still an ongoing discussion.

Read more here.