Discover Performance

HP Software's community for IT leaders // November 2013
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Real business value lies in connecting your data

And it’s not just about getting value—it’s about surviving against new competitive challenges.

The bottom line

What: All your data needs to connect.
Why: The Big Data payoff is in quickly getting, and acting, on new insights.
How: Every IT project has to improve, not hinder, data connections.
More: Get our free ebook, “Connecting data for new business insight” (reg. req’d).

The new mantra for the whole enterprise—and as a result, IT—has to be: “Everything needs to connect.” There’s a strategic shift going on as organizations struggle to capture value from the 2.5 quintillion bits of information we create daily. Success in Big Data is about more than pulling insights from large data sets: it requires connecting the right pieces of data to create the right vantage point in the first place.
 
Sure, at a basic level, you need to have the tools to govern and manage all that data, but do you want that to be your legacy: “My data didn’t overwhelm me”? Or do you want to be known for having enabled your organization to connect the dots and provide intelligent answers that matter? Every move you make should be aimed at reducing the time and cost required for Big Data to help conceive, build, and test a hypothesis and make better decisions. Do this across the enterprise, and you enable non-IT executives to connect ideas like real-time consumer sentiment, customers’ engagement, weather events, and changing market opportunities to predict the next hit product or even the next crime wave.
 
“Every decision you make about bringing in new systems or information, you have to think carefully how the data will connect with other information sources,” says Paul Muller, vice president of strategic marketing with HP Software. “A CxO has to say, ‘Nothing goes into my environment unless it can be understood, massaged into a common format, indexed, and then connected to all other data.’”
 
Many CxOs have undertaken siloed analytics projects, data warehousing, or enterprise search projects that focus only on the immediate questions they’re asking of that data in frame, instead of the questions which might be answerable if systems with diverse information types could be linked and analyzed, regardless of location or format.

Focus on the future

Whether you’re working with advanced analytics today or still building a capability, you have to start now to architect a connected intelligence strategy that supports such an effort. Ask yourself:

  • Can your data repositories automatically create context?
    For example: “Can I tie my Radian 6 data back to my call center data and customer databases without having to throw out my old analytics and business intelligence tools?”
  • Can your data be made available securely?
    For example: “Can data analysts with access to my financial data also see my R&D data? Can I anonymize personal information without loss of fidelity?”
  • Can you integrate 100 percent of your information?
    For most organizations, 90 percent of the fastest growing information is the least utilized because of scale and automation challenges, such as automating the classification of images, audio, and video. For example: “Can I leverage digital call-center recordings and social mentions, as well as buying patterns, to learn more about high-value dissatisfied customers?”
  • Can you work with data wherever it lives?
    “Do I have to move my data to one place to analyze it, or can it stay in-situ?” The latter saves valuable time and network resources.

Think it through

“With so much innovation in social, consumer, and enterprise technology, we are all in a constant state of catch-up,” Muller says. “Just when you think you’ve related all forms of data, another comes along. The answer is to be proactive about architecting your Big Data platform to be flexible in the face of constant change.”
 
From there, you can demand real insight.
 
“Simple search and retrieval is now a pretty mundane thing,” says Autonomy VP Brian Weiss. “We’re at the point where we need, and have, the tools to analyze complex data types and deliver automatic insights very similar to the way humans think. Understanding information in its context can drive automation, and incredible value, well beyond a better set of search results for an end user.”
 
But this level of connectivity and integration is not accomplished overnight. Most IT practitioners don’t think of data outside of the application that owns it. It simply may not occur to them that there is tangible value in having a framework that looks at all data in the same context, and can apply policy to information, whether it resides in SharePoint, in the cloud, or in public sources related to the business. In contemplating Big Data initiatives, we must think wide, as well as deep, about our information targets and ambitions for delivering insight.
 
With the ability to find contextual connections between data, wherever it resides, and by interacting with it in a common format, you can thoroughly and quickly connect the dots between data across your organization—linking activity between CRM systems used by marketing, reporting systems used by sales, profitability tracking applications used by finance, help desk tickets, log files, and the actual interactions with your customers who call your help desk, send emails, and opine in social media about your company and products.

Demand real, immediate connectivity

Vendors will tell you at the outset that they can “seamlessly connect” any data across your disparate infrastructure. They may even claim that they can integrate structured, semi-structured, and unstructured data. But you may find out later that to make those connections, you need to convert all your data into a proprietary format, or move the source content into a centralized system. That’s more cost, more waiting, less flexibility, and less time to innovate.
 
The model that requires a CxO to move custody and control of a type of data to be able to understand it will not keep up with the pace of innovation. The move and load times alone are an obvious barrier, but more importantly, we want the data to stay in the systems of record. We need connectivity to analyze and control data in context with other live information sets.
 
By making it intuitive and easy to see how all of your data connects, you’ll place your organization in a much better position for applying intelligent analytics to derive value from diverse data sources. After all, the CIO is perhaps the only one in an enterprise who understands data outside of the app that owns it, the database that stores it, or the network that delivers it—and this is an ideal vantage point for thinking of data in terms of the potential value it offers.  

Read our companion interview with Brian Weiss about mastering human information.  For more on crafting a next-generation Big Data strategy, download our free, original ebook, “Connecting data for new business insight” (reg. req’d).


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