Join Barton Poulson for an in-depth discussion in this video The three Vs of big data, part of Big Data Foundations: Techniques and Concepts.
- Big data is an ambiguous and relative term. It may be best to define it by what it is not. It's not regular data. It's not business as usual. It's not something that an experienced data analyst may be ready to deal with. To put it another way, big data is data that doesn't fit well into a familiar analytic paradigm. It won't fit into the rows and columns of an Excel spreadsheet. It can't be analyzed with conventional multiple regression, and it probably won't fit on your normal computer's hard drive anyhow.
On the other hand, one way of describing big data is by looking at the three V's of volume, velocity, and variety. These come from an article written by Doug Laney in 2001, and they're taken as the most common characteristics of big data, but they're certainly not the only ones. We'll talk about some other possible V's to consider in big data later in this course. Let's start by looking at the first of the three V's, volume.
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- What makes big data "big"
- Understanding how big data impacts consumers, businesses, and research
- Exploring the intersection of data science and big data
- Facing big data's ethical challenges
- Understanding the sources and structures of big data
- Storing big data
- Prepping big data for analysis