- Value : Various types of information can have different complexity for perception and processing issues, making it complex for intelligent systems to work with. So, the information must be managed in such a way that it delivers value eventually.
- Veracity: It stands for provenance or reliability of the information source, its context, and how significant it is to the analysis based on it.
- Variety: Information in arrays can have heterogeneous formats that can be structured partially, completely, and accumulated. For instance, social media networks use Big Data Analysis in text, video, audio, transactions, pictures, etc.
- Volume: First of all, the data is measured by its physical size and space it occupies on a digital storage medium. The “big” includes arrays over 150 GB each day. Moreover, you can use the Data Catalog to understand your collection of information well.
- Velocity: After that, the information is regularly updated, and real-time processing requires intelligent platforms and technology.
Additional V’s of Big Data
Other characteristics and properties are as follows:
- Visualization means collecting and analyzing a huge amount of information using Real-time analytics to make it understandable and easy to read. Without this, it is impossible to maximize and leverage the raw information.
- Validity: It means how clean, accurate, and correct the information is to use. The benefit of analytics is only as good as its underlying information, so good data governance practices should be adopted to ensure consistent data quality, common definitions, and metadata.
- Volatility: It means for how long the information should be kept because before Big Data, there was a tendency to store information indefinitely because of its small volume; it hardly involved expenses.
- Vulnerability: A huge volume of data comes up with many new security concerns since there have been many big data breaches.
- Variability: Some data streams can have peaks and seasonality, periodicity. Managing a large amount of unstructured information is difficult and requires powerful processing techniques