If CMDB adoption is in the first full blush of morning light, then analytics remains still in the dim, shadowy world of pre-dawn light. Yes, there's light on the horizon, or just below it, and yes it's better than the "Hour of the Wolf" situation (e.g. roughly 4 a.m.) that the market was in probably four or five years ago, but vendor focus in analytics remains scattered and dim.

This is based on the results of the first EMA, and quite possibly first ever, research on analytic technology adoption within the IT management market - spanning service assurance, service-level management and business service management, optimization and capacity planning, security, storage, configuration, process automation, and asset management and chargeback.

However, this is not to say that there aren't vendors passionately aware of analytic requirements for real-time, or near real-time, and historical capabilities - there are certainly a handful of these. In the broader area of managing application and service delivery across the infrastructure (network and/or data center centric), analytics really seem to be taking hold. Out of the 37 companies that completed the survey, a full 20 support something to do directly with assuring services and optimizing infrastructure in support of service delivery. The other areas (actually all related to this requirement logically) capture significant results - with security showing the second strongest play.

The reasons for this are partly pain points. If analytics are the "super weapons" in solving issues around IT service delivery, then they're being most aggressively applied to those areas in the IT service management wars where pain and threats remain most visible and imminent. And that's in service assurance.

By now, I suppose it's past time to clarify just what I mean by "analytics," so here goes. EMA defines "analytics" as "a set of algorithms or functions applied to static or dynamic data collected from IT infrastructure or external sources to enable IT management processes." Basically it's the intelligence that transforms management data into information that's relevant and usable. That information can be applied to these management processes:

* Data gathering - gathering relevant vs. random data.
* Relationship modeling - building effective configuration and topological and application dependency information.
* Storing data in how relationships are modeled.

Denise Dubie is senior editor with Network World.