What Are The 4 Vs Of Big Data? (With Big Data Definition)
Updated 30 September 2022
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Currently, the real value of several tech companies relies on their data, which is information they are constantly analysing to adjust their products according to their customers' needs and expectations. These organisations usually collect data from their customers, potential clients and competitors to create new products and services that can satisfy different types of consumers and participate in various industries simultaneously. Understanding the key characteristics of big data can help you explore career options in this field and improve your knowledge of tech companies.
In this article, we determine the four key features of big data, discuss what big data is, and explain how organisations use big data.
What are the 4 Vs of big data?
The 4 Vs of big data are volume, velocity, variety and veracity, which are the key characteristics you may consider knowing if you are managing regular data or big data. The world's biggest tech organisations are continually collecting data because this information enables them to increase their efficiency or discover new market niches. The data they analyse may have explicit or intrinsic value as sometimes they can use it to address an immediate need or file it, hoping to discover later more key information from it. Processing all the data they collect may require complex computer programs.
For example, a car manufacturer located in Tamil Nadu can conduct an online study among its customer to know their preferences regarding leather-made seats. If the company sends some surveys to customers located in a particular area in India, they might handle this simple data with regular software. It might be a totally different situation if the company opts to obtain answers from their customers and potential consumers around the world. To be able to analyse and use big data for improving a company's activities, it is essential to know how to identify it. Here are its key features:
Volume refers to the amount of data a company can receive from its customers, potential users, indirect clients, suppliers, employees, competitors, markets and operations. A large volume of data demands better technology to collect, process, store and analyse it. By using devices such as desktops, laptops, tablets, smartphones, or machines placed at train stations, airports or entertainment centres, people are generating data incessantly. This has encouraged new ways to handle data and digital places for storing it. For instance, a company may establish a business-to-business (B2B) relationship with a supplier to store the digital data it is receiving.
Big data is usually too large to manage through regular computers. It may require special technology created with this purpose and capacity. Currently, megabytes, terabytes and petabytes are insufficient data measurement units to handle the information organisations are receiving from several sources.
Related: Top 20 Big Data Tools: Big Data And Types Of Big Data Jobs
Velocity refers to the speed with which multiple sources produce data, which means how fast a source is generating data a computer can process instantaneously. For example, think about how many text messages people send every day in India or how many they can send across the world. A text message represents digital data that travels incredibly fast through satellites that are floating in outer space, huge antennas, receivers and a smartphone. The data travels so fast that the user feels that everything is occurring in real time, but behind this process, a system is processing trillions of messages simultaneously.
Related: What Is Big Data Hadoop? (Definition And Career Opportunities)
Variety refers to the type of data an organisation may receive and process. There are three types of data, which include unstructured, semi-structured and structured. A system manages information according to the type of data is receiving, which means it can apply different algorithms and require distinct types of storage based on the data.
For example, text messages, short video files, audios or images represent different types of data. A system can process structured data by applying defined rules, while it can handle semi-structured data by using rules and conditions. To process unstructured data, systems use flexible conditions and multiple frameworks simultaneously.
Veracity is perhaps the most valuable feature of big data because it adds credibility and quality to the information a company is receiving and processing. If a company uses data with high veracity levels to support several business decisions, may reduce the opportunity for misleading outcomes. For example, a pharmaceutical company can decide to launch a new drug based on data obtained through experiments and trials.
Data with low veracity comprises pointless information that can lead to erroneous actions within a company if it decided to use it in its decision-making process. Businesses usually discard non-valuable data, also known as noise, because it can consume time and effort. For example, a shoe retailer may receive reviews from customers across the world, but it cannot use this information to launch a promotion because the company operates only in Hatia, Jharkhand.
Related: 18 Big Data Examples (Common Uses In Different Industries)
What is big data?
Big data refers to the large amounts of information produced by different sources and processed by different systems that measure their volume, velocity, variety and veracity. This information can have a numeric structure that systems can process and store easily, or have unstructured and dissimilar forms that require flexible frameworks. For example, videos files are forms of unstructured information. A system cannot quantify this type of big data because each file contains a large amount of diverse information. A single message in a social media account may contain sound files, images, video files, numbers, location and multiple hyperlinks.
Organisations usually employ specialised technology that divides big data into data sets to collect, classify and analyse the information quicker. These systems can store the info in databases that all departments throughout the organisation can check to perform their activities. Currently, cloud technology allows people around the world to share information in real-time, so the specialised technology processing big data is currently working to store everything in the cloud. This is expanding companies' locations, as they may have a virtual presence across the world and recruit employees that can access the same information without sharing a physical workplace.
Related: 10 Characteristics Of Big Data And How You Can Use Them
How does an organisation use big data?
Organisations can collect and use big data in different scenarios, as they can apply this information to all known industries. Here is a list of how companies and governmental institutions may use big data:
If a large corporation starts a hiring process to fill several job positions within the organisation, they may receive thousands or millions of applications. This can be possible because numerous candidates throughout India and sometimes across the world can send their resumes and cover letters, looking for the hiring manager's attention. A computer program usually filters all applications within a given period, discarding those that do not have the basic requirements for the role. It also identifies those who may have the exact educational background or experience the company is looking for and classifies them according to their abilities.
This process that often occurs in seconds might require several days or months if the corporation did not employ big data technology.
Currently, a government can use big data technology to conduct a census, which is an enumeration of women, men, children, companies, houses, cars and demographic data. This information is essential for governments to address regional or national issues, plan long-term budgets, allocate resources, monitor their birth rate or propose more open immigration policies. A government used to require months and years to collect and process all the information gathered manually. Big data technology is facilitating the way governments get information from their citizens, because it is enabling them to analyse the data quicker and plan and act faster.
Marketing agencies use big data technology to explore and analyse potential markets for their clients. They can conduct digital surveys, analyse how customers interact with the client's social media accounts, process reviews posted on several online platforms and review the complaints they receive by email. Big data allows a marketing agency to process all the information in seconds, but also helps it plan marketing campaigns to target a certain group of customers or improve the overall public image of the client. With big data technology, a marketing agency can monitor the results of an advertisement in real-time.
A stock exchange produces enormous amounts of data every day. Investors across the world can participate in the market without being physically present in the building where the stock exchange operates. This is possible because the stock exchange is currently operating online, which means it is producing data constantly. Big data technology collects all investors' bids, analyses them and delivers outcomes in real-time. It also provides each investor with access to valuable and transparent information that enables them to make business decisions.
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