A recent article in the NYTimes: How Not to Drown in Numbers by Alex Peysakhovich and Seth Stephens-Davidowitz, highlights the benefit of taking an approach to the analysis of big data which was also inclusive of the insights that smaller, more individualized sources of data can provide. The article focused on ways that Facebook (and other companies using big data) have merged quantitative as well as qualitative data sources to create deeper understanding of not only what is happening, but also why.
What does this mean for the field of evaluation? I think this quote sums things up nicely. “We are optimists about the potential of data to improve human lives. But the world is incredibly complicated. No one data set, no matter how big, is going to tell us exactly what we need. The new mountains of blunt data sets make human creativity, judgment, intuition and expertise more valuable, not less.” There will continue to be great value in the use of mixed methods for collecting data and use of diverse data sets from which to draw meaning and there will certainly continue to be a need for skilled evaluators and researchers who can help to make sense of all the data, big and small.