Big Data, Big Concerns, and Shakespeare

摘要

As I tour campuses, the biggest concern I hear about our profession is the onslaught of big data. Many statistics departments are concerned that students, grants, and allocations are going to the quickly growing data analytics curricula. We also hear other terms used in place of big data such as data analytics, data mining (perhaps so yesterday), machine learning, data science, knowledge discovery, business intelligence, informatics, and even money science. Typically, big data is identified by the three Vs of velocity, volume, and variety. I have been informed there are now up to 42 adjectives starting with V that describe it. I'm not sure I could think of 42 words starting with V. Apparently, many people do not like to use the term "big data," perhaps because it might be demeaning to work with the opposite. But I am also unsure what the opposite might be. What happens if you have huge volumes of data with lots of variety, but they don't necessarily come in with rapid speed? Does two out of three still let you join the big data club?