What are the characteristics of Big Data
The following three are known as “Big Data Characteristics”.
- Volume
- Velocity
- Variety
Volume:
Volume means “How much Data is generated”. Nowadays, Organizations Human Beings, or Systems are generating or getting a very vast amount of Data say TB(Terabytes) to PB(Petabytes) to Exabyte(EB) and more.
The name Big Data itself is related to its size which is enormous. The size of data plays a very crucial role in determining the value of data. Also, whether a particular data can be considered as Big Data or not is dependent upon the volume of data. Hence, ‘Volume’ is one characteristic that needs to be considered while dealing with Big Data.
VOLUME = Very large amount of data
Velocity:
Velocity means “How fast data is produced”. Nowadays, Organizations Human Beings, and Systems are generating huge amounts of Data at a very fast rate. The term ‘velocity’ refers to the speed of generation of data. How fast the data is generated and processed to meet the demands determines the real potential of the data.
Big Data Velocity deals with the speed at which data flows in from sources like business processes, application logs, networks, social media sites, sensors, mobile devices, etc. The flow of data is massive and continuous.
VELOCITY = Data produced at a very fast rate
Variety:
Variety means “Different forms of Data”. Nowadays, Organizations Human Beings, and Systems are generating a huge amount of data at a very fast rate in different formats. We will discuss in detail about different formats of Data soon. Variety refers to heterogeneous sources and the nature of data, both structured and unstructured.
During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Nowadays, data in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. are also being considered in the analysis applications. This variety of unstructured data poses certain issues for storage, mining, and analyzing data.
VARIETY = Data produced in different formats
Three “Vs” Paradigm (Volume, Velocity, Variety) of Big Data was defined by “Doug Laney” in 2001.
If our Organization’s Data is in this 3V Paradigm, that means we are in Big Data Problems. So we should use some Big Data Solutions to solve our problems.
This 3Vs Paradigm is not enough to get better value from our Big Data. There is another V (4th V), which is most important for every Big Data problem.
4th V: Veracity
Veracity means “The Quality or Correctness or Accuracy of Captured Data. Out of 4Vs, it is the most important V for any Big Data Solutions. Because without Correct Information or Data, there is no use in storing a large amount of data at a fast rate and in different formats. That data should give the correct business value.
This refers to the inconsistency that can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively.
VERACITY = The correctness of data So this 4th V answers the following questions:
How accurate is that data in predicting business value?
Do the results of a big data analysis make sense?
Big Data 4Vs In Simple Terminology:
V(Volume): The Amount of Data
V(Variety): The number of Types of Data
V(Velocity): The Speed of Data Processing
V(Veracity): The Correctness of Data