Infosys-Oracle Blog : Cloudanomics for Business Intelligence

Guest post by
Swati Maskara, Senior Associate Consultant, Infosys

The Economics of Cloud Computing is by now well established with its claim to reduce cost, improve efficiency and decrease time consumption when a cloud environment is used by a business.

With respect to Business Intelligence there is a need to understand dynamics of cloud computing for performing business analytics. The article intends to do so by addressing few questions around Cloud computing:

How Cloud qualifies as an efficient platform for performing Business analytics?
How is Cloud model different from SaaS?
How organizations can derive maximum value from a Cloud setup and what are the major challenges?

The article discusses these aspects in detail to bring forth the view point that Cloud model for performing BI is undoubtedly going to restructure and modernize IT within organizations.

How Cloud qualifies as an efficient platform for performing Business analytics?
With respect to BI, Cloudanomics provides the ability to perform advance and complex analytics on terabytes of data stored on the cloud infrastructure and deliver management reports.

Cloud Computing- The off premise arrangement
Cloud Computing offers significant cost and efficiency advantages by providing the customers with the hardware, software, security and required domain expertize needed to create and manage huge data marts and data warehouses. The data marts created are then linked to computational tools available on the cloud facilitating business analytics. The analysis is made available to the customer by integrating the reports generated on the cloud with client's environment. This requires a defined data integration and BI Strategy.
Cloud Computing- The Benefits
Cloud customers are relieved from investing upfront in storage space for creating data marts, acquiring and upgrading the computational tool to perform analytics, required manpower or licensing the software. These are made available by the vendor on a pay-as-you-use basis. Data marts created using Cloud infrastructure can be cancelled after the business requirements are met and the hardware and software deployed becomes available to be used elsewhere. This ensures optimum utilization of resources by the software companies.

How is Cloud Computing different from software as a service (SaaS) model which already provides on demand BI solutions to customers?

Following are fundamental differences:-

SaaS delivers an application as a utility whereas the Cloud delivers computing as a utility. Cloud customers can make use of advance computing technology available on the cloud
SaaS model is based on Multi-Tenant Data Architecture whereas Cloud customers have dedicated servers for storing their data
Cloud customers have greater control over server settings and hence ensuring greater security

Hence Cloud platform ensures enhanced data security, improved ability for analytics and greater control.

How organizations can derive maximum value from a Cloud setup and what are the major challenges?

Apart from the above advantages Cloud Computing for BI can come very handy for mid-size businesses and Non Profit Organizations where the analysis is usually performed by either using alternate low cost BI tools or the traditional spread sheets. Also industries facing a seasonal demand for analytics can make use of Pay-as-you-use Model. Cloud platform can also be leveraged to provide a medium to the client for evaluating and testing various technologies. Organizations need to learn how to derive maximum value from a Cloud setup.

Cloud technology for performing analytics however, has to deal with issues around data security and data integration. Businesses are often reluctant to share sensitive information on the cloud. There is a need for the vendors to design products which meet the quality and integrity standards required by the clients before they place mission critical data on the cloud. Also there has to be a clear data integration and BI strategy in place for the reports and information to be delivered back to the enterprise as and when required since the availability of accurate and timely information defines the thrust for any BI tool.

With more and more organizations using Cloud platform for performing analytics, the inhibitions of businesses will also decrease, however there is a need for vendor maturity in order to provide clients with better and more efficient platform for performing informed analytics and improve the quality of services.

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Comments

Good read Swati. I have always maintained that irrespective of the business you are in now, it is imperative to look at a "hybrid" model(public+private) option for "utilizing"(i highlight this as moving to the cloud is NOT equal to cutting costs on the resource front) the efficiencies it has to offer. But, that said there are still apprehensions amongst various businesses to move to a successful model until and unless it is proven! Cloudalytics makes more sense given that mobility is widely prevalent now but then this would require various businesses to come together to provide an industry standard and agree upon non-monopolistic and non-encroachment of IP when collaborating together. Collaborative Intelligence is how Cloudalytics can be defined to help organizations move forward.

Posted by: venkat | September 6, 2011 9:38 AM

Thanks Venket. I agree with you that as far as industry standard is concerned there is a need for vendor maturity in terms of quality of services and development of Cloudalytics as a product. Innovation and product development along with a third party arrangement for ensuring data security is going to play a major role in future.

Posted by: Swati | September 7, 2011 12:38 PM