In the modern digital world, almost everything revolves around data. Our daily activities on internet-connected devices collect data, making it our most valuable resource. This data is particularly valuable to businesses that can process and analyse it with advanced tools for their own benefit. Many world's largest organisations, such as Google and Amazon, rely on data to drive their operations and increase profits. However, the broad category of data, also known as Big Data, can be further classified using the 4 V’s of Big Data.
According to Domo, 2.5 quintillion bytes of data are created each day. However, not all data created on the planet can be processed and analysed for the benefit of organisations. Those looking to capitalise on vast data resources use a type of data with specific characteristics known as Big Data.
This blog will shed light on what Big Data is and the four Vs of Big Data
Table of Contents
1) Understanding Big Data in Detail
2) What are the 4 V’s of Big Data?
a) Volume
b) Velocity
c) Variety
d) Veracity
3) What is the fifth V?
4) Conclusion
Understanding Big Data in Detail
Big Data could be defined as a large amount of registered digital data on the internet. It refers to the massive amount of information generated by sources like social media platforms, weblogs, sensors, etc.
Big Data can be classified as structured (like DBMS tables), semi-structured (like XML files), or unstructured (like media such as audio, videos and images). Big Data deployments can consist of terabytes, petabytes and exabytes of data collected over a period. Companies or organisations aim to convert this data into valuable insights.
Until 2011, Big Data was considered expensive to manage and complicated to derive value from. However, this definition is not exactly up to date as the concept has seen a lot of changes over the years. Today, creating value with Big Data is much easier, thereby debunking the outdated definition.
Yet, Big Data is not always defined correctly or clearly, as not many people know its exact definition. While most people know what data is, they do not know the characteristics of data that make it ‘Big’. To clarify the concept of Big Data, International Business Machines (IBM) devised the theory of the four Vs, all of which define and characterise Big Data as it is.
What are the 4 V’s of Big Data?
Big Data is generally defined by four major characteristics: Volume, Velocity, Variety and Veracity.
Volume
As we know, the first characteristic of Big Data is its Volume. Trillions of gigabytes of data are created worldwide every day, and the numbers will only rise in the years to come. Most of this massive quantity of data generated daily is due to the widespread use of mobile phones.
Text, photos, videos and applications create lots of data every day, and it will only increase with mobile phone use in the coming years. As the Volume of data sees exponential growth, new database management systems and IT employees will be needed to handle it. As a result, millions of new IT jobs are expected to open in the coming years – thanks to the Volume of Big data.
Velocity
Velocity, or speed as many would call it, is the second characteristic of Big Data. It refers to the unprecedented speed at which data is generated and processed. The data is processed instantaneously if you send a text or post anything on social media such as Facebook, Twitter or Instagram.
Processing and surfacing information once was a time-consuming process, but with the advent of the internet – it takes next to no time. However, this is not just because of the internet but also of the existence of data. The more the data is created, the more methods are required to handle it, and the more data is monitored – thereby creating a cycle.
Variety
The first and second characteristics of Big Data correlate with the third character, the Variety of Big Data. As we know, data is large in volume and fast to process – and at the same time, data comes in many types. Organisations and individuals generate and process data according to their specific needs, ensuring a wide Variety of data on the planet.
IT solutions are available to almost all sectors, from business to banking and the medical to the sports industry. Nearly every organisation in every sector keeps a database, contributing to a wide Variety of data. When the internet reaches the farthest corners of the world, the Variety of data will only increase.
Veracity
The final characteristic attributed to Big Data is its Veracity. Veracity can be defined as conformity to facts or accuracy, and it refers to the element of accuracy that data possesses. The Veracity of Big Data refers to the data's trustworthiness and denotes the data's accuracy and quality.
Data quickly becomes outdated, and with its abundance, it is tricky to determine the authenticity of everything you see. This is why many upper-level businesspeople do not dare make decisions only on data. This also grants impetus to data Scientists and IT Professionals to organise and process the right data to use it correctly. The higher the Veracity, the more importance the data holds as it is set to be analysed and converted to meaningful information.
What is the fifth V?
While the four V, as mentioned earlier, are the most common characteristics associated with Big Data, a fifth V often goes under the radar. The fifth important element of Big Data is its Value or significance. Data, when organised and processed in the right way, can be converted into valuable information.
In the modern data-driven ecosystem, organisations that do not create a data strategy will likely fall behind their counterparts. Organisations that use their data profit much more as data provides important understanding and context of customers. Contextualised data provides insight into customer behavioural patterns, how to optimise business operations and to improve service delivery.
Regardless of how it is used, the fact that data creates value when used correctly is a very important element. This is why organisations, regardless of size or industry, should adopt a data strategy to ensure that they are profiting from the valuable data.
Conclusion
Though data is an umbrella term that defines information compiled for reference or analysis, any data with the 4 Vs of Big Data as their characteristics are classified separately. With a large volume and variety of Big Data available, its Veracity must be tested before converting it into meaningful information.
In other words, high Volume, high Velocity and high veracity data should be processed using advanced tools to create value. Big Data can also improve inefficiencies in the supply chain, predict market trends and future needs, and promote innovation. Organisations have endless potential if they can harness and use the data properly to give themselves a competitive edge over their industry counterparts.
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