Approximately 3 quintillion bytes of big data are generated each day from the different information sources which is a huge amount and indeed difficult to handle. To know which information is useful further and which is useless, we need filtration and this filtration is not an easy process. It requires efficient information handling processes in information-intensive systems of organizations.
It’s ok if you don’t know.
Now tell me how you will define big data?
Well, not certainly!
Various factors decide whether the information is big or not. In this blog, we will tell you 4Vs, and with the help of these Vs. But before talking about that, we will know what big data is and what 4 Vs of big data.
What is Big Data?
Big data is really useful for the business organization because with the help of this information they extract the important information and use it in their business operations and decision-making processes. Organizations can estimate the latest trends and patterns from this information in order to grow their business.
In order to analyze and process information, we need its size, and for that, we apply volume dimensions to it.
Approximately 70-80% of unstructured information exists, and its overall volume is continuously rising.
Velocity refers to the pace at which we consume information. The volume of information is reciprocal to the value as the volume increases; it decreases the value of individual information points over time.
For instance, 500 million call details records are analyzed in real-time to estimate the churn quickly on a regular basis. The velocity of high information generation requires different processing methods.
Moreover, the velocity of information determines the potential of information. It analyzes how fast the information generation and processing are to meet the requirements.
information sources generate different types of information categorized into three-part: Structured information, unstructured information, and semi-structured information.
Here, structured information is all about bank statements such as Information, amount, time, etc. Comparing unstructured information with structured information is a great way to understand it.
No specific rules are associated with unstructured information like structured data, but with the help of advanced technologies, we can transform unstructured information into structured data.
The veracity of Big Data
Veracity implies the quality of information that we are going to analyze. In data analysis, high veracity information records have proved their power to make it valuable. Veracity is directly proportional to valuable Information; high veracity refers to meaningful information, whereas low veracity information indicates meaningless information.
Moreover, the velocity of information determines the potential of information. It analyzes how fast the information generation and processing are to meet the requirements. For instance, 500 million call details records are analyzed in real-time to estimate the churn quickly on a regular basis. The velocity of high information generation requires different processing methods.
The higher the veracity, the more important the information is and provides us with valuable outcomes.
In this blog, we have talked about the 4Vs of big data and makes the information really big. I hope you found this article useful in the context of Important Vs of data and V features of data.