Tuesday, July 3rd, 2012 - OVUM
OVUM COMMENT: Denise Montgomery, Ovum Research Director Financial Services Technology

Insufficient attention is being paid to how and when the back-end applications that supply the data will be real time-enabled and integrated. While much time and money has been spent on building “industrial-strength” business intelligence (BI) environments, they continue to be designed and implemented in batch environments and are neither timely nor agile. Lack of clarity around realtime use cases, the level of investment required, legacy issues, and a profusion of new vendor offerings is resulting in end-to-end realtime enablement being deferred or consigned to the “too hard” basket.

Organizations are now starting to embed BI in operational processes as a way to react quickly to customer demands and unexpected events, and gain competitive advantage. To be effective it must operate at a transactional pace and be able to analyse realtime data streams that reflect the current state of business. Ovum believes “realtime” is best construed as having the appropriate interaction data quickly enough to affect the interaction to which it relates. The terms “realtime” and “near-realtime” in the retail customer interaction environment have hence become, in effect, interchangeable. This is in contrast to the financial markets arena, in which competitive pressure is pushing requirements for ultra-low-latency (sub-sub-second) transactions.

The immense volumes of “Big Data” generated from increasingly unstructured data sources, such as remote machine sensors, social networks, multimedia, video streaming, and the digitization of value exchange, is estimated to reach 8 zettabytes by 2015. Methods of interrogating this data are being piloted, or productionized, in most banks, but the processing of this data is not necessarily fast. In most cases it is being done offline, as humans and machines search for patterns and relevance in the data. These insights then need to be operationalized in a faster more responsive environment. This may mean the coding of decision rules in realtime applications or machine-to-machine learning environments. Either way, the volume of data increases as the response time for the use of this data decreases.

-ENDS-

Contact Profile

OVUM


Ovum provides clients with independent and objective analysis that enables them to make better business and technology decisions. Our research draws upon over 400,000 interviews a year with business and technology, telecoms and sourcing decision-makers, giving Ovum and our clients unparalleled insight not only into business requirements but also the technology that organisations must support. Ovum is an Informa business.
Jennifer Duraisingam
P: +61 3 9601 6723
W: www.ovum.com

Keywords

While much time and money has been spent on building “industrial-strength” business intelligence (BI) environments, they continue to be designed and implemented in batch environments and are neither timely nor agile.

Categories

Sharing

More Formats