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HP Software's community for IT leaders // November 2013
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Make Big Data work for Ops

Big Data presents a big challenge—but also a big opportunity for Operations leaders.

The bottom line

What: Get a better, more connected view of your data to improve IT operations.
Why: Data blind spots mean you can’t meet expectations, which breeds shadow IT.
More: Learn about harnessing data on HP’s Operations Analytics page.

Most enterprise IT shops have spent years building business logic to handle the data that flows into the enterprise, powering automated processes that minimize manual work. Yet this structured data now accounts for just 10 percent of all data that comes into the enterprise. Thanks to the cloud, social media, email, sensors, and an increasingly mobile user base, the other 90 percent is unstructured data pouring in around the clock from humans and machines alike.
 
Now that the era of Big Data is upon us, many enterprises face a conundrum: they’re sitting on a mother lode of strategic information, but mining it for insight is an enormous challenge. As you look at not merely coping with Big Data but delivering better services from it, you will need visibility into that untapped 90 percent. Here’s how to get the visibility you need to harness the power of Big Data and put it to work for you.

Transformation

The first step in this journey is to automate routine IT operations tasks. Instead of taking up expert resources, you can use the business logic with structured data to execute rapidly and consistently, avoiding the risk of manual errors and any resulting downtime.

After you’ve automated tasks, you can begin to tie them together and create end-to-end processes and workflows that remove manual hand-offs between teams. Now you can provision secure services within minutes. IT can transform its operations and let the business adopt newer business models.

Delivery

Even when IT can automate the tasks and processes that enable services, it can’t necessarily deliver in a timely and efficient way. Without the needed efficiencies, the business will procure its own services outside your purview. You can’t prohibit shadow IT from taking ground if you need three weeks to set up a service that the  business requests—and that the third party can deliver in a few minutes.
 
The next step is to move from a reactive to a proactive approach to delivery, and uncover insight hidden in unstructured data. With that insight, you can move closer to a ticketless IT environment. For example, human-generated social data can feed back into help-desk processes with the relevant context, allowing the business user to quickly understand the problem and even fix it. The application of social insight helps fine-tune the process of addressing the fixes, to significantly drop the time it takes on average to resolve an issue.

Assurance

Today, most organizations are doing basic monitoring. But to provide assurance that services will run reliably, you need more than the basics. You must bring all of your war rooms together to share data, enabling you to pinpoint a problem anywhere and make sure the necessary person knows how to address it. Then, the insight hidden in Big Data can help you predict problems before they arise next time, so you can eliminate perfect storms before they develop.

From challenge to opportunity

When you have blind spots in your data, you’re unable to meet expectations. And when you can’t meet expectations, the business decides to solve its own problems—bringing in services that you didn’t vet, but still have to support when something goes wrong.
 
Big Data may be the answer to this problem, because it holds the key to understanding what users need. When you can capture and analyze all of the unstructured data flowing into your environment each day, you’re better able to close the gap between business expectations and your ability to deliver. Big challenge? Yes. But Big Data presents a much bigger opportunity for those organizations willing to use it.
 
For more on harnessing data to improve operations, visit HP’s Operations Analytics page.


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