The promise of big data

On bringing together two different approaches to research—By Tim Fisher

As a curious six year-old, I studied each nook and cranny of the farm where I grew-up. I felt intimately familiar with every element of the landscape. Then, one day, my mother showed me an aerial photograph of the farm and it reshaped my understanding of the place where I lived. Some details on the photograph were new, but inconsequential——I hadn’t known that the metal roof on the barn was a patchwork of rusted corrugated steel. But, other details challenged my previously held assumptions. The scale of the buildings was different than what I had known; the house was smaller, the barn looked massive. And, while I had always assumed that the farmland itself was a giant rectangle, the aerial view clearly showed that the plot was triangular in shape. I now had two ways to see my world—an “on the ground” view that was filled with richness and nuance, and a view from above that helped me to place my understanding in a broader perspective.

In studying humans—their thoughts, feelings, behavior and relationships, I have come to depend on two, very different approaches. First, I have been drawn to the “on the ground” perspective offered by qualitative methods like ethnography. And, I have been fascinated by the “aerial view” offered by quantitative inquiry because it provides a glimpse into the population as a whole. The two approaches are different, but complementary; the strengths of one compensate for the weaknesses in the other. While quantitative methods enable a researcher to make generalizable insights, they tend to lack the richness and nuance that can be obtained through a qualitative point of view.

I’ve found myself immersed in quantitative and qualitative methods at different points in my career, but rarely at the same time. A decade ago, I taught qualitative methods to university students. Then, I spent four years in jobs that required daily number crunching with quantitative analytical tools like Excel and SPSS. Now, I’ve come back to a focus on qualitative approaches and am immersed in ethnography and in-depth interviews. Each of these experiences has asked me to focus entirely on one approach or the other. It’s as if quantitative and qualitative methods are squabbling children in the back seat of a car, asked to sit apart, each given their own toys to play with and told that they’re special in their own unique way. When one gets more attention, the other gets defensive.

The emerging field of “big data” has the potential to subvert the traditional distinction between qualitative and quantitative research. It can offer both breadth and depth simultaneously. It makes it possible to analyze numerical data points as well as text, photographs and videos. It’s also introducing new ways to think and talk about how we go about understanding the world around us.

There is something almost ethnographic about the way that big data recedes into the background and quietly collects data about our lived experience.

In the big data world, everyday life—whether mundane or special—is transformed into data. Mundane tasks like grocery shopping, commuting, or writing an e-mail leave digital “traces” that are captured and transformed into data points. And, the types of data being collected are ever-expanding as the world becomes more digitized and sensors are embedded in household objects. Because the processes of capturing data are automated, they do not make a distinction between the mundane moments and those special or sacred moments that might be guarded as personal or private.

There is something almost ethnographic about the way that big data recedes into the background and quietly collects data about our lived experience. Big data observes, takes notes, and analyzes the world as people carry-on their day-to-day lives. And like an ethnographer who spends a long time in the field and eventually blends into the surroundings, we get used to big data’s presence and can become more comfortable and familiar with it over time. But, the invisibility of data collection can present significant ethical and analytical issues—people often create content and use data with an intent that differs markedly from those who collect and analyze it.

While people may officially opt-in to the world of big data, the devices and platforms that collect data are increasingly essential elements of everyday life. We use them as the primary way to connect with our closest relationships. We rely on them for basic information. And they are often the main tools we use in our work. In fact, it may be nearly impossible to be employed in the knowledge economy without also having your everyday activities captured, stored, and analyzed. Working in most organizations requires e-mail usage, web searching, and cell phone use, activities and interactions that are transformed into data. Opting out of the world of big data may be theoretically possible, but not feasible or desirable.

The advent of big data has been described as a promising new era that will reveal different kinds of insights about our world. Compared with other forms of data collection that take a snapshot of data at a single point in time, the technologies of the big data era are capable of capturing aspects of human activity on a continuous, second-by-second basis. These technologies give us a window into human activity and interactions that were previously impossible to analyze with such accuracy and detail.

Despite all the promise, the current world of big data has been criticized for being shallow. (It is important to note that big data is an ever-evolving field that is becoming more sophisticated all the time.) Beyond mere technological advances, the promise of big data may more likely be fulfilled in a new interdisciplinary world that brings together experts in technology and analytics (e.g. Data Scientists) who are grounded in the tools of the trade with social and behavioural scientists who have deep knowledge of the dynamics that shape human thoughts, feelings, behaviours and relationships. The benefits of connecting these disciplines could be significant. Together, they could generate new ways to think about how to design, access, analyze and make sense of data—each discipline bringing their unique expertise to the table. And they could create, for instance, new insights about complex human phenomena, like social networks, that have been previously difficult to study (see Rupert 2013).

The aerial photograph still hangs in the farmhouse and I stop to look at it once in a while. As an adult, the vantage point continues to fascinate me, but I also know what the picture fails to capture—the texture of the weather worn house, the foot paths etched into the grass or the subtle changes in elevation around the property.

Now, my understanding of the farm is based both on a close-up view that celebrates the richness and nuance of the property and buildings and the knowledge of how the farm fits into the landscape and community. A challenge and opportunity in the development of big data will be bridging these two vantage points—the high-level, aerial and the on-the-ground and idiosyncratic to create a richer understanding of human experience.

Tim Fisher is currently a director of insights and strategy at a company based in Toronto. He holds a PhD in sociology from the University of Southern California. Previously, he taught in the Department of Sociology at Wilfrid Laurier University in Waterloo, Ontario.

Share Tweet about this on Twitter Share on LinkedIn Google+ Google+ Email to someone
TAGS /big data / qualitative vs quantitative /