Commentary

Four Big Data Misconceptions

Big data is quickly becoming a bigger buzzword in 2013, and it clearly cannot be ignored by today's marketer. However, as with all new developments, that same marketer is probably left wondering exactly what big data is and how it can be used. We are collecting more data than ever before, but we have faced a real challenge in pulling that data out of storage and using it to drive action. This is where big data comes in -- and here are some common misconceptions that marketers should be aware of.

Misconception #1: Big data is a new concept

When Bill Gates made the famous comment, “640K ought to be enough for anybody,” the year was 1981. At that time, 640K (that's about what it takes to store 30 seconds of your favorite song these days) of customer records would have been considered by most to be "big data." Big data is really just what happens when the technology we use to capture, store, analyze, and use it begins to have trouble with the volume and types of data that define our new reality. We have adjusted before, and we will certainly need to adjust again.

Right now, traditional technologies like relational databases and tools ranging from Excel to enterprise business intelligence that worked very well with yesterday's volume and types of data are no longer a perfect fit for the vast, unstructured data that is rolling in every second of every day. We are simply at a pivotal point where new types and sizes of data require new thinking and new solutions.

Misconception #2: Big data is just technology

We've had the pleasure of working with some very big, very complex data sets from some of the world's biggest brands, and what may surprise you is that we rarely see cases where a complete technology deployment and overhaul is needed to handle big data sets. Far more often, we will see opportunities for easy wins using new analysis concepts and tools to better analyze existing data.

Tools such as Tableau Software allow a new type of flexibility in manipulating, analyzing and mining data sets, while a new realm of dashboarding tools like Klipfolio can connect to and help surface and visualize virtually any type of data, whether it is owned, on a laptop hard drive or in the cloud.

Misconception #3: Big data is magical

Investing in new technologies is useless without a skilled and experienced team to properly utilize these tools to support strategic planning and action. It's like buying a private jet and forgetting to secure a captain and crew: there is no magic button to push that makes your new jet fly itself. And more than that, big data is as much a mindset as a collection of technology, tools and techniques.

Shifting an organization toward a data-driven culture requires a path to data maturity. Models, such as Stephane Hamel's OAMM, can help organizations understand where they sit with respect to management, technology and methodologies that can help structure a path to attaining organizational goals surrounding big data.

Misconception #4: Big data doesn't apply to me

Companies can be surprised at just how much data they are generating. When thinking about Web data, customer data, sales data, process data, resource data, etc., even the smallest organizations can find themselves reaching a point where big data analysis & techniques can offer some very tangible results. A small restaurant, for example, might be able to optimize its pricing, hours, coupon strategy, email marketing lists and even its menu, and larger organizations with richer data sets can achieve much more by taking advantage of big data techniques.

Companies today have unprecedented access to ever growing amounts of data, but the challenge of big data is being able to leverage that access and use it to provide tangible value. Successful companies are not only deploying and integrating technical solutions -- they are putting in place the organizational infrastructure, skills, and teams necessary to activate that data.

While defining and progressing down a path toward leveraging big data to inform marketing decisions offers a competitive advantage today, it will be nothing short of essential for survival tomorrow.

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