11 Ways to 'Game Plan' for Big Data

 
 
By Dennis McCafferty  |  Posted 09-18-2014 Email
 
 
 
 
 
 
 
 
 
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    Assess the Current Data Culture
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    Assess the Current Data Culture

    Collaborate with all business users—such as analysts, data support teams and marketing execs—to get a sense of existing pain points that new approaches and solutions can address.
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    Inventory Resources
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    Inventory Resources

    Evaluate available technologies and determine what systems, storage and network assets must be upgraded—then present a business case for these deployments based upon proven ROI.
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    Secure Buy-In for Change
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    Secure Buy-In for Change

    It's one thing to come up with new strategies to take advantage of big data. But if leaders and stakeholders aren't willing to make the necessary changes to respond, then it's a waste. The business case helps greatly here.
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    Assemble the Right Team
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    Assemble the Right Team

    Your "coach," for example, could be a consultant or firm with a distinguished track record in analytics. Your "quarterback" is a business-side exec who can keep everything focused on strategic outcomes. Your "linemen" are the folks in the trenches who can get the job done.
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    Begin at the End
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    Begin at the End

    Make sure from the start that teams are focused on the needed outcomes. Goals must determine technology, not the other way around.
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    Build Incrementally
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    Build Incrementally

    Make sure you're introducing a new capability at least every three to four months.
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    Know What to Leave Out
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    Know What to Leave Out

    It's not about gathering all the data you can. It's about gathering all the data that will lend strategic, meaningful insights.
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    Incorporate Firm Oversight
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    Incorporate Firm Oversight

    You should have clear requirements for collecting and cleansing the data, as well as classifying it and defining its relevance.
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    Consider In-Memory Computing
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    Consider In-Memory Computing

    Ranked by Gartner as a top 10 strategic tech trend, in-memory computing improves real-time, data-driving decision-making by eliminating high latency and the need to access data from disk-based storage.
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    Expand Through NoSQL
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    Expand Through NoSQL

    NoSQL enables high-performing, high-availability storage at Web scale, so IT can manage massive data streams with rapid response times.
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    Always Look Ahead
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    Always Look Ahead

    Historic data is very useful. But even more so when it supports predictive analytics to forecast what business trends to expect in the future.
 

By now, CIOs realize that there's potentially endless value in big data. The road to analytics deployment, however, is lined with many pitfalls, as seven of 10 of these initiatives fail to achieve their anticipated value, research findings reveal. Clearly, any success here depends upon a number of variables—including many that have little to do with technology. It's safe to say, in fact, that analytics initiatives represent the primary means for CIOs to demonstrate their capabilities as business-impacting leaders. With this in mind, we're presenting the following best practices to help you come up with a winning game plan for big data. They have been compiled from online resources posted by Information Control Company (ICC) and Intel. While several are tech-focused, the majority address the strategic side of the equation. "Any major technology initiative … demands a sound strategy aligned with your business goals," says Steve Grover, vice president of business analytics at ICC. "[Data] is not simply the latest shiny object to be enjoyed for a while, then tucked away discreetly when it doesn't fulfill expectations that were never properly defined." For more insights from ICC on big data, click here. For more about the best practices from Intel, click here.

 
 
 
 
 
Dennis McCafferty is a freelance writer for Baseline Magazine.

 
 
 
 
 
 

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