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Why the ideal data center is like a restaurant kitchen


G10706008072009_JPGHighres.jpgThere’s no question Big Data is changing the way enterprises operate and compete, particularly with using Big Data for business decision making. In the fast-moving consumer world we live in, companies want to try three or four variations, see what sticks, and get rid of the rest.


For instance, say you’re Staples or some other retailer of office supplies. The window for back-to-school shopping is fairly short, a few weeks at best. So you want to put a number of features on your website, create a number of different customer interactions and see which one generates more sales. The goal is to try something, get data back and make changes almost in real time.


Except it’s not happening. And here’s why.


The bottleneck in your data center

Most enterprises don’t have a way to turn ideas into features quickly. If the business goes to IT and says, “Hey, I want to make four changes, and I’ll probably get rid of three of them,” IT will most likely come back with, “Are you crazy?!”


Thanks to Big Data analytics, the business knows which things are working. But IT can’t change fast enough. This is where automation comes in. (Check out this infographic)


An automated, orchestrated data center is key to taking advantage of the insight provided by Big Data. Because now you need to go from inception to production as quickly as possible. If you’re Staples, trying to capitalize on the one back-to-school promotion that is generating incredible sales, you need automation. Sending emails and asking people to make changes just isn’t fast enough. You have a short amount of time to gain insights from systems of engagement and profit from them.


Big Data changes everything

In most companies it’s difficult to make rapid changes to production systems. But Big Data is putting pressure on enterprise systems to become faster. At HP we have a saying, “Big Data changes everything.” Big Data is going to change the way the data center operates.


This change ties into the theory of constraints. The first constraint used to be, “I don’t have the data” so I don’t know what’s working. That’s no longer true.


So now you move to the next bottleneck, which is the application release process. You can’t get changes to applications out quickly enough, so you work on that. This is what DevOps is all about - taking an idea and quickly making it real.


When you solve that problem, you move to the next constraint.


Why the ideal data center is like a restaurant kitchen

Here’s what you should strive for as you work on removing bottlenecks: the data center as a restaurant kitchen. Imagine, for a moment, that you’re a chef in a restaurant. You have an idea and everything you need—ingredients, pots, pans, cooking tools, refrigerator, stove, and so on—is there for you to make it a reality. So one night, for instance, the fish is not selling well, then you can easily change course and make a pasta. Depending on what your idea is for how best to serve your customers you can come out with an omelet, a salad, a steak … It doesn’t matter, because you have the machinery of cooking in place. All you need is an idea and a feedback loop.


When your data center is orchestrated, the only thing you need to change each time is the idea.


To learn more check out the HP Toolkit for Implementing Automation (registration required).



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