Strategy: Predictive Analytics for IT

Mar 01, 2012


Just Like Magic

Let's be honest: Even when we could get clean data, crunching numbers manually has never been a winning value proposition for IT. In the mainframe era, it meant lots of pricey actuarial elbow grease. In the age of single-server, single-application architectures, infrastructure fragmentation made it prohibitively costly and difficult to build data silos filled with accurate transactional information on which to perform analysis.

But virtualization and the cloud model have changed everything. Like bell-bottom pants, centralization is back. And unlike yesterday's fashions, it's streamlined. With pervasive virtualization, it's suddenly possible to have both centralization and role-based server provisioning. You can have single-server, single-application rollouts on consolidated hardware with centralized management and excellent availability of operational data.

This smarter centralization has paved the way for the cloud paradigm and brought the basic principles of scalability, elasticity, resilience and sometimes multitenancy into vogue. It's also enabled IT-focused predictive analytics software that can see changes and learn and respond by constantly re-evaluating mathematical and predictive models. Once these systems build trust, they can bring automation into the cloud era.

In this report, we'll delve into how these systems work and why some companies can't ­afford not to deploy predictive IT analytics. (S4530312)

Research Report