The Vs of big data are three main concepts the term is associated with and characterized by: volume, variety, and velocity.
- Volume. Big data deals with analyzing large amounts of low-density, unstructured data, like Apple collects information on user preferences or Spotify determines the music taste of users. This might amount to hundreds of petabytes of data.
- Variety. More data sources imply more data in more formats, ranging from traditional documents and databases to semi-structured and unstructured data from GPS location data, social networks, search engines, etc.
- Velocity. Data is generated, collected, and processed, and the world expects it to be done quickly. The data frequency of generation and the frequency of data handling, recording, and publishing are two types of velocity in relation to big data.
The characteristics of big data are not limited to the three Vs. You may also come across such properties as veracity, value, variability — other Vs — as well as exhaustiveness, scalability, and more.
Big data refers to vast and complicated data sets that are created and collected in real time from multiple sources.
Data mining is the process of uncovering patterns and insights from large datasets. It uses statistical and mathematical methods to analyze data and find relationships, trends, and anomalies.