TeamQuest to Discuss a Five-Year Data Center Capacity Sourcing Strategy at Gartner Summit and Conference
Service disruptions can damage customer loyalty and sully brand reputation. At the Gartner Data Center Summit and Conference, TeamQuest will discuss how to avoid downtime in the long term through proper capacity sourcing.
IT departments have long been relegated to the land of “no.” For management, they can be seen as a limiting factor for expansion — a “why we can’t do this” department — rather than a stimulant for growth. Yet that’s all changing, as current IT strategies are becoming sink-or-swim imperatives for companies across all verticals. If capacity planning strategies fail and companies experience downtime, customers are quick to flock to other providers and services, no matter the quality of the brand.
Later this month, TeamQuest will present at the prestigious Gartner Data Center Summit in London, as well as at Gartner’s Data Center Conference in Las Vegas. And while we’re there, we’ll also discuss how to determine an effective five-year capacity sourcing strategy. Joined by industry titans like CISCO, Intel, and Oracle, TeamQuest representatives will shed light on how businesses can organize IT into a holistic, management-aligned endeavor.
While the path to determining a five-year data capacity sourcing plan will vary from company to company, one of the biggest mistakes all companies should avoid making is treating IT as a series of disjointed processes.
Some have described this as the Elephant in the Dark Room Dilemma — one large problem is attacked by a group of people who each use separate, narrowly defined methods and terminologies. It’s inevitable that the end result will be inchoate and unclear. When capacity planning is the goal, companies need to conceptualize IT from a broader business perspective.
There are two generally accepted practices for bringing IT’s disparate information under one roof: ETL (Extract, Transform, Load) and Data Federation. Many companies will use a combination of both, and either strategy allows for performance collection and analysis in bulk. Using this information, companies can make predictions about future data usage rates and infrastructural needs (whether they be localized servers or viralized packages).
Far from static numbers, those requirements must be updated on a regular basis to keep predictions and IT buys in line with business objectives and needs. To do this, most companies will choose an IT capacity planning tool that makes use of both simulated and predictive analytics.
This allows businesses to keep running forecasts and update their infrastructure as needed. Most importantly, automated analytics prevents companies from making human errors, and it can reveal a level of insight that would be too resource-intensive for most human analysts to provide.
IT departments and the businesses they support work best when both operations run in concert. Merging information silos allows decision makers to weed out unnecessary applications and systems and plan for IT service spikes, eliminating costly and brand-damaging downtime. Then, the resources gained from reducing bottlenecks can be funneled towards projects that will best suit the company at large.
Five years down the line can seem like a long time in a constantly evolving digital landscape, but companies that design performance-related strategies are the ones that will most effectively channel their resources and keep satisfied customers on board. Learn much more about the must-have items in any data sourcing strategy by catching TeamQuest’s discussions at this year’s Data Center Summit and Conference.