##Six Provocations of Big Data

In the section titled “Bigger Data are Not Always Better Data”, I agree with the authors’s points that just because a sample size is large doesn’t always mean that its representative data. I think that this point ties in well with previous readings as we have discussed big data being too large to work with due to its difficulty in filtering and interpreting. However, how can we ensure that our data sets are representative and not too fixed at the same time?

In the section titled “Just Because it is Accessible Doesn’t Make it Ethical”, if big data is so large and lacking in depth, then I question the author’s point on whether someone should be included as a part of a large aggregate of data. The researcher is not likely analyzing every data entry individually, so it’s interesting to see the author questioning “What does it mean for someone to be spotlighted or to be analyzed in a way the author never imagined?”