He wasn't joking. While big-data is arguably the buzzword of the year, defining it continues to be a source of endless consternation. So what's real? What makes sense? Here are three perspectives that define, discuss, and help to focus the role of big-data today.
Big-data is how we get to the right message, to the right people, at the right time, on the right platform, on the right place. Oscar Padilla, VP of Strategy, Luminar
Luminar is an analytics and modeling provider that serves the US Hispanic market, with a goal of "transforming Hispanic consumer data into true insights and business intelligence." At the recent Portada Annual Conference, Padilla noted that big-data can help marketers reach their goals and make an effective sell of everything, from credit cards and hair-care products to automobiles and political messages.
Big-data is enabling marketers to accelerate their growth through more relevant and precise data models, he said. In other words, it's creating opportunities for "big analysis" that can provide greater accuracy, more practicable analyses, and improved performance and forecasting.
Big-data is a relative concept. What is big today won't be big tomorrow...
But big-data isn't about that. It's a story about the meaning, the challenges, changes and opportunities that it represents. Patricia G. S. Florissi, VP and Global CTO, EMCDuring a recent presentation at Worcester Polytechnic Institute in Worcester, Mass., Florissi predicted the era of big-data we will trigger changes similar to the ones that occurred during the Industrial Revolution, with some industries ceasing to exist, new ones being created, and others reinventing themselves.
Those trying to police what is or is not big-data will often do so based on what their interest, sphere of influence, knowledge or experience and jobs depend on. Greg Schultz, Founder, Server and StorageIO
In a post entitled "Little data, big data and very big data (VBD) or big BS?" he noted, "Big-data is not BS, however there is a lot of BS marketing BS by some along with hype and fud adding to the confusion and chaos, perhaps even missed opportunities."
While "big-data is real," he writes, there are variations, use cases, and types of products, technologies, and services that fall under the big-data umbrella. In addition, it is wrong to characterize all data as big-data. "What this all means is that there are different types of applications for various industries that have big and little data, virtual and very big data from videos, photos, images, audio, documents, and more."
How do you define big-data? Do you agree with any of the points these data pros made?