What are some examples of the Three V's of Big Data? The three V's stand for: volume, velocity, variety.

Three V's of Big Data, provided by Norwegian University of Science and Technology.


3 Answers 3


Simply stated, big data is to big to work on one computer. This is a relative definition, as what can't work on today's computer will easily work on computers in the future.
- One Google search uses the computing power of the entire Apollo space mission.
- Excel used to hold up to 65k rows in a single spreadsheet. Now it holds over a million.

Data is coming in extremely fast. Traditional scientific research methods of a few hundred cases could take weeks, months or even years to analyze and publish.
- Iris flower data set
- Statistical Programming Language R
- Twitter Firehose (6,000 tweets per second)

Big Data that is contained in one specific data type or does not fit well within the format of a relational database. This data often comes in the form of unstructured text.
- Estimated 80% of all enterprise data is unstructured
- Open Data(Government)
- noSql Databases

Iris Data Set: https://en.wikipedia.org/wiki/Iris_flower_data_set
Open Data: https://www.data.gov/open-gov/


Actually, it is four V's which define Big Data.

An answer of mine on CrossValidated to a similar question explains the four V's.

As @MikeStratton has neatly explained the three V's, I would explain the fourth V, which is Veracity.

Veracity is the uncertainty in data.

Examples can be poor data quality, inadequate data from surveys, etc. This makes the fitted models highly biased and error-prone.

You might also want to have a look at this discussion.


IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. This infographic explains and gives examples of each.


And also this one picture beautifully summarizes whole Big Data and above two answers with one example covering all the parameters. http://www.ibmbigdatahub.com/infographic/four-vs-big-data


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