What is Data? What is Big Data?
There are many different classes of data types. Within the context of this guide, we will mostly be considering quantitative, machine-readable data.
You may be most familiar with the following:
- numerical data (e.g. prices, measurements, coordinates)
- boolean (logical) (i.e. "TRUE" or "FALSE")
This term is sometimes used vaguely. Most often, it means:
- extremely large collections of data -- so large they they can only be interpreted computationally (see: Pence, "What is Big Data?")
- analytical methods employed to interpret large data sets
- approaches to decision-making, which are informed by analyses of large data sets
Big Data as seen by IBM -- this site presents some key aspects of big data very clearly.
Parts of this guide were adapted from the excellent guide (http://libguides.mit.edu/ssds/
Jennie Murack, Geospatial Data Librarian and Statistics Specialist at MIT Libraries, whose kind permission I herewith gratefully acknowledge.
READ THIS FIRST
This guide contains information for the 2016-17 Common Reading Program at AUC:
Big Data – What is Your Digital Footprint? (The readings are linked on the right.)
In order to engage in a conversation, we have to agree on the words we use. So ....
- Look at the definitions of "data" and "Big Data" in the box on the left
- Take this quick tutorial and quiz to learn about QUANTitative and QUALItative data.
- Watch the short video below to learn what "data science" is about
- Consider some basic ethical issues related to Big Data analysis (video: BBC / summary: IBM / essay: NIH)
... then, explore the tabs above to learn more. Enjoy the program!