In our previous post, Defining Big Data, we highlighted the difficulties in defining the term Big Data. We left off by stating that even though the term may be ambiguous, the phenomenon it is trying to describe is significant. Its implications will not only be limited to modern tech-firms but will also have effects reaching into other industries, and other areas of society.
There are some fairly well known examples of how big data, and big data analytics have resulted in innovations. In 2005 Google wanted to see if they could predict flu outbreaks in the US based on search patterns from their search engine, and so the prediction tool Flu Trends which at one point provided more successful estimates of outbreak than the US Center for Disease Control (CDC). At LinkedIn, big data helped create the popular features ‘People You May Know’ and ‘Jobs You Might Be Interested In’. However, it turns out that big data will impact areas of business far removed from the tech-labs of Silicon Valley as well.
Big Data in sciences
The influences of Big Data are aiding many fields of science especially those requiring massive data collection and analysis. In a recent article titled, The Big Challenges of Big Data, we see how Big Data is disrupting and innovating the field of biology. Especially in the study of gene regulation, drug development and the evolution of genomes, where handling, processing and sharing data is of vital importance. With the aid of Big Data, studies are no longer limited by the immediate access to supercomputers and advanced instrumentation, labs are able to capture, access, and analyze terabytes of data at unprecedented speeds. Smaller labs and research institutions around the world are now able to produce results at the same speed and volume as their larger and more well financed counterparts.
Over turning scientific models
In Wired Magazine’s article, The End of Theory, we see how massive amounts of data and applied mathematics will affect all areas of society. Every theory on human behavior can now be tracked and measured with never before seen fidelity. With this type of data, scientific analysis may not need to be scientifically driven, the possibility exists that computing algorithms may discover what science cannot.
“But faced with massive data, this approach to science — hypothesize, model, test — is becoming obsolete.”
-Chris Anderson, Editor in Chief Wired Magazine
Society and understanding
When big data is applied to social science in this way, the results may be very interesting. In Critical Questions for Big Data we see that Big Data offers many of the humanistic and social science a new way to quantify their studies and become more objective. It may even reframe the process of research and how information is interpreted by these fields.
Big Data is already having transformative impacts in many different fields, some of which we know more about because they make headlines in the news, others we know less about because they might not obviously be of business value. Since we are still in the early days of this trend it is reasonable to suspect that most significant impacts are yet to be seen. Is it possible that the scientific method will have to be reevaluated on the basis that big data-driven simulations may one day replace actual empirical observation? Such a scenario is not unrealistic. We know examples of how tech-giants like LinkedIn and Google have developed innovations from big data, but as the tools and capabilities become more prevalent throughout industry, will more traditional organizations also be able to leverage its potential?
As we work to complete our master thesis, we plan to explore the concept of Big Data and possible applications to Innovation, and share what we learn in future posts. In order to complete our study, we are currently seeking individuals who are experts in Data Analysis and/or Innovation. If you are interested in joining our study, or know someone who may be, please contact either Niclas Zachrisson or Robert Urbaniak at email@example.com or firstname.lastname@example.org.
Big data innovation info session
Niclas and Robert are planning an event at the end of May, where they will present and discuss the major findings of their Master Thesis. Keep an eye out for a “save the date-post” where more information will be provided.