(You might consider a fifth V, value.) High-volume, high-velocity and high-variety of Big Data . with more detail . IV. In data science, this is often referred to as data cleaning, this operation is frequently the most labor intensive as it involves all of the pre-work required to set-up the high-performance compute. Time is a determinant factor along with rate of spread. This is where the vast majority of errors and issues are found with data and this is the fundamental bottle neck in high-performance computing. Nowadays big data is often seen as integral to a company's data strategy. Data Veracity, uncertain or imprecise data, is often overlooked yet may be as important as the 3 V's of Big Data: Volume, Velocity and Variety. In recent years, Big Data was defined by the “3Vs” but now there is “5Vs” of Big Data which are also termed as the characteristics of Big Data as follows: 1. Big data’s power does not erase the need for vision or human insight. These characteristics highlight the importance and complexity required to solve context in big data. Big data has specific characteristics and properties that can help you understand both the challenges and advantages of big data initiatives. Let me first introduce 8 V’s of Big data (based on an interesting article from Elena), namely Volume, Value, Veracity, Visualization, Variety, Velocity, Viscosity, and Virality. Recent developments in sensor networks, cyber-physical systems, and the ubiquity of the Internet of Things (IoT) have increased the collection of data (including health care, social media, smart cities, agriculture, finance, education, … To determine the value of data, size of data plays a very crucial role. C HARACTERISTICS, I SSUES A ND C HALLENGES. Viscosity - Viscosity measures the resistance to flow in the volume of data. Big data analytics has gained wide attention from both academia and industry as the demand for understanding trends in massive datasets increases. In most big data circles, these are called the four V’s: volume, variety, velocity, and veracity. Q. The general consensus of the day is that there are specific attributes that define big data. You may have heard of the three Vs of big data, but I believe there are seven additional important characteristics you need to know. While I don’t feel like adding all the V-words to the 3 or 4 V’s definition of Big Data, these new two, viscosity and virality, sound intriguing. Consider the following statements: Statement 1: Volatility refers to the data velocity relative to timescale of event being studied. Virality measures how quickly data is spread and shared to each unique node. Volume is a huge amount of data. Volume: The name ‘Big Data’ itself is related to a size which is enormous. Volume The main characteristic that makes data “big” is … Statement 2: Viscosity refers to the rate of data loss and stable lifetime of data Validity, Volatility, Viability, and Viscosity of Big Data . If we closely look at the questions on individual V’s in Fig 1, they trigger interesting points for the researchers.