Big data is a phrase that we are hearing more and more in the digital age, but what do we really mean when we say it, and what do we mean by big and by data?
In a presentation given as part of the panel ‘Big data made simple: How to cut through to crucial analysis’ at the Futurebook Conference 2016, Ian Mulvany, Head of Product Innovation at SAGE Publishing, attempted to explain what we mean by big data and what we can do with it- all in 5 minutes! And so on the last day of Love Your Data Week we’re sharing his insights:
What is big data?
Big data is a term used to describe an extremely large volume of data that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
For social science researchers, this offers new opportunities to listen to millions of voices, observe billion of interactions, and to analyse patterns at a scale never seen before in order to gain new and exciting understandings of the social world.
These new opportunities are not without their limitations, and what these new and vast data sets have created is an increase in the number of occasions where a researcher reaches the limits of what is technically possible to them to achieve. By breaking down these barriers, and creating new tools to address this skills gap, researchers can really begin to cut through to find real and tangible answers to important social questions.
How do you use big data and for what purpose?
There are different ways of analysing big data which includes: sorting vast amounts of data into manageable databases, using online tools to formulate predictions based on various inputs, as well as making connections between various different data points. How you approach big data depends on what you are trying to achieve through the analysis. Below are three examples of how you might use big data analysis for different purposes:
Learning about the possibilities of big data and working through the current challenges that social scientists face when looking to engage in this type of research is key to helping the researchers of tomorrow. Through working through the challenges now, we will be in a better position to tackle the tough sociological questions through the applied use of big data research.
Ian Mulvany joined SAGE Publishing in September 2016 as Head of Product Innovation. He is responsible for supporting the development of tools that can help social science researchers work with big data. Ian can be followed on Twitter @IanMulvany and blogs at http://partiallyattended.com.
This post is part of our Connection series for Love Your Data Week (February 13-17, 2017), an annual international event created to foster conversation and build awareness for quality research data management. Find other posts in the series here. You can keep up-to-date with our latest activities by following @SAGE_News, @SAGElibrarynews and #SAGEDataWiz. And join the data conversation on social media by using the official Love Your Data Week hashtags #LYD17 and #loveyourdata.