The promise of Cloud enabled Analytics

The promise of analytics is all too familiar. The ability to optimize traffic flow in realtime, conduct fraud and risk detection as transactions are taking place, understand and act on customer sentiments in social networks among many others. Analytics has truly evolved from a business initiative to a business imperative.

In IBM's 2011 CIO study, a majority of CIOs ranked Analytics as the #1 factor contributing to an organization's competitiveness. A 2011 study conducted by IBM Institute of Business Value and MIT  Sloan Management Review confirmed that organizations that embraced analytics were 2x as likely to outperform their peers.

Recently, we have witnessed a shift of focus from Enterprise Data Analytics to Big Data Analytics. This is being accelerated by the significant amount of data being generated daily; 12 terabytes of tweets, 5 million trade events every second, thousands of video feeds from surveillance cameras etc. A quote from John Naisbitt summarizes the state of today's economy very well...“We have for the first time an economy based on a key resource [Information] that is not only renewable, but self-generating. Running out of it is not a problem, but drowning in it is.”

In this new economy, there is a need for complementary approaches to Analytics to handle these new  sources of data. Traditional sources of enterprise data, which are usually structured and logical can be handled quite effectively by Transactional, ERP and Data Warehouse Systems. Emerging Sources of unstructured data, e.g. machine generated data like RFID, log data and data from sensors, or Cloud Data which is typically includes a combination of text, multimedia and other forms of unstructured data, require a platform tuned to their unique workload characteristics. There is therefore a need to develop capabilities that bridge the need for Analytics on structured and unstructured data.

The emergence of these trends has shifted IT into the center of business, but IT faces challenges realizing the value Analytics can deliver. Due to the increasing complexities of IT infrastructure, most organizations are unable to shift budgets away from maintaining and operating existing systems. The increasing data volumes, formats and sources of data is driving the need for new solutions that minimize complexity and reduce time to value.

Cloud computing can minimize these barriers and reduce complexity through standardized service delivery. Clouds computing platform optimize investments through a shared infrastructure with elastic scalability to handle variable workloads. This results in a faster time to value. 

IBM's PureData System accelerates cloud adoption. PureData System is optimized for very high transactional throughput and high speed peta scale analytic and transactional data workloads. IBM clients are using PureData System for Database & Analytics workload consolidation on a highly scalable and resilient infrastructure.