The Five Vs of Big Data
Big Data can be split into five sections which can help determine how the data is used. These sections are often referred to as the "five Vs" which are volume, velocity, variety, veracity and value. Volume is concerned with the amount of data that is collected, produced and analysed. If the amount of data collected and produced is not a large amount, then it is not considered to be Big Data. Velocity is the speed in which data is collected and produced. If data is collected at a fast pace, it allows algorithms to be adjusted quicker. Variety is the range of data collected and produced. There are three main categories regarding variety, these are structured data, semi-structured data and unstructured data. Structured data is data that can be analysed by computers or people since it is neat and easy to navigate. Semi-structured data contains both structured and unstructured data, therefore some of the data can be analysed by people but the more unstructured parts have to be organised by a computer. Unstructured data is data that has little to no organisation. Examples of these types of data are numbers and dates, log files, and pictures and videos respectively. Veracity refers to the accuracy and how trustworthy data is. Before the data is processed, the accurate and inaccurate data must be separated to achieve better results. Value refers to how useful the data is, the data must be relevant to purpose. For example, there would be no point in a car manufacturing company gathering data on what ice cream flavours are rising in popularity, as it's not relevant to the company's operations. From a business perspective, taking all of these factors into consideration allows organisations to create better algorithms and marketing techniques to increase sales.

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