Introduction Big Data
Big data has gained popularity among numerous associations and can be more helpful for businesses like banking, online businesses, insurance, manufacturing, and so forth to entice their clients. When the volume of the data was low, older technology could usually easily manage and process it. These systems are ill-suited to handle it because big data differs from regular data in terms of volume, velocity, and value. In terms of its features, such as volume, velocity, variety, value, virality, volatility, visualization, viscosity, and validity, researchers and practitioners have identified, characterized, and investigated big data. In this essay, the fourteen features of big data have been found and defined.
Big data is defined as data that is more varied, arriving at a faster rate and in larger volumes. The three Vs are another name for this.
Why is the big data real example useful?
Transportation: help with traffic, weather, and GPS navigation. Track tax, defense, and public health data in the government and public administration. Business: Reduce costs and streamline management processes. Access medical records for faster treatment development in the healthcare industry.
EVOLUTION OF 14 V’s AND 1C OF BIG DATA CHARACTERISTICS
A. 3 V’s of Big Data
Big data is a novel concept, and many scholars, organizations, and people have given it different definitions. Volume, Velocity, and Variety are the three V’s that industry analyst Doung Laney (now with Gartener) used to define big data in terms of in 2001.
B. 4 V’s of Big Data
Variability and Complexity are two new dimensions added to SAS (Statistical Analysis System). The four Vs — Volume, Velocity, Variety, and Veracity — have also been used by Oracle to define big data.
C. 5 V’s of Big Data
Big data was explained by Oguntimilehin. A in terms of the five Vs: volume, velocity, variety, variability, value, and complexity.
D. 10 V’s of Big Data
Kirk Born characterized big data using the 10 Vs in 2014 for Data Science Central, which stand for volume, variety, velocity, veracity, validity, value, variability, venue, vocabulary, and vagueness.
E. 14 V’s of Big Data
For researchers and practitioners to manage big data efficiently, these qualities offer a research horizon. To manage and use big data efficiently and effectively, the entire field of study on big data is centered around these features. But there are still certain gaps that must be filled to gain a deeper understanding of the subject.
All of the properties of big data have been mentioned and defined below.
A. Volume:- quantity of information gathered and kept. Data is in TB units.(Size of Data)
B. Velocity:-The speed at which data is sent from source to destination.(Speed of Data)
C. Value:- It symbolizes the potential business value of big data.(Importance of Data)
D. Variety:- At the receiving end, many types of data including images, videos, and audio arrive.(Type of Data)
E. Veracity:- If the analysis of the acquired data is inaccurate, it is essentially useless.(Data Quality)
F. Validity:- Information that was extracted from the data was accurate or correct.(Data Authenticity)
G. Volatility:-Big data volatility refers to how long the user can use the stored data.(Duration of Usefulness)
H. Visualization:- It is a method of representing intangible ideas.(Data Act/Data Process)
I. Virality:- The rate at which data is broadcast or distributed by one user and received by other users for their use is what is meant by this term.(Spreading Speed)
J. Viscosity:- There is a time discrepancy between the actual event and what is being described.(Lag of Event)
K. Variability:- Data is continually being generated from various sources, and how well it can distinguish between significant and noisy data.(Data Differentiation)
L. Venue:- Different sorts of data came from various sources using various platforms, such as the personnel system and private and public clouds.(Data Platform)
M. Vocabulary:- Data structures and data models are examples of data nomenclature.(Data Terminology)
N. Vagueness:- Information that was vague regarding the truth or showed little to no consideration for what it would mean(Indistinctness of existence in data)
O. Complexity:-Data arrives from various sources, and in order for information to spread fast, it is vital to identify any changes, no matter how small or significant, with respect to the data that has already been received.(Correlation of Data)
Big data is a collection of data sets that is always expanding since data is produced by everyone and for every purpose, including contact centers and mobile devices. This essay focuses on big data and the V’s (volume, velocity, value, variety, veracity, validity, visualization, virality, variability, volatility, venue, vocabulary, vagueness, and complexity) that characterize it. The challenges that are being reported daily show that the amount of research currently available is insufficient to handle and process big data. Verbosity, voluntarism, and versatility are the three new ‘V’ traits that have been identified as a result of the study that is given in the paper. The study of the 17 V’s and 1C (volume, velocity, value, variety, veracity, validity, visualization, virality, viscosity, variability, volatility, venue, vocabulary, vagueness, verbosity, voluntariness, and versatility) identified characteristics is anticipated to offer simple and efficient management of big data that can be used in value-added applications and research settings.
n my article I have mentioned only the introduction of big data and its evolution of 14 V’s and 1C of big data characteristics and the possibility of its development. In the following next article, write a type of big data ,why it is important ,How big data works and additional information.
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