At the beginning of the 20th century when big data was first introduced, it was spoken of using the three V’s: volume, velocity and variety. In the course of time, two additional V’s (value as well as veracity) were added to help data scientists to become more efficient in articulating and communicating the essential features associated with big data. In this blog, I will tell you about the 5 V’s of Big Data in detail. So, let’s get started!
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What Is Big Data?
Big data is the combination of semi-structured, structured, or unstructured structured data that organizations collect. The data can be used to uncover insights and is used to create machine learning, forecasting modelling and various other advanced analytics applications.
Data from big databases can be utilized to improve efficiency, offer better customer service , and design targeted marketing campaigns -all of which can increase the value of your business. For instance, big data could give companies valuable insight on their customers. This information can be used to improve methods of marketing to improve customer engagement and conversion rates.
Big data can be utilized by companies in the energy or medical sectors, for instance. Medical professionals can use big data to determine the risk factors for disease and can also be utilized by doctors to assist in the diagnosis of ailments among patients. The energy industry could make use of big data to monitor electric grids, implement risk management, or to perform real-time analysis of market data.
Companies that make use of big data could have an advantage over those who do not, as they are able to make more efficient and informed business decisions because of the information.
The 5 V’s Of Big Data
Let’s take a look at the 5 V’s of Big Data:
Volume
Volume is the first of the 5 V’s of big data, refers to the volume of data in existence. Volume is the basis of big data because it is the first size and quantity of data collected. If the amount of data is sufficient then it is classified as big data. What constitutes big data is dependent but it will alter based on the available computing power available.
Velocity
The 5th 5 V’s in big data are velocity. It is the speed at which data is created and how fast that data flows. This is a crucial aspect for businesses that require their data to move quickly so that it’s accessible in the appropriate timeframes to make the most effective business decisions.
A company that makes use of big data will experience an enormous and constant flow of data being produced and delivered to its destination. Data can come from various sources like machines smartphones, networks, and social media. These data streams must be processed and analyzed rapidly and, sometimes, in near real-time.
For instance, in healthcare, there are numerous medical devices that are used for monitoring patients and collect information. From medical equipment used in hospitals as well as wearable medical devices the collected information must be transferred to the correct location and rapidly analyzed.
In certain instances there are situations where it would be more beneficial to keep only a small amount of data rather than collecting more information than the company can handle, because this could lead to slowing down data velocity.
Variety
The final V in the 5 Big Data V’s is the word “variation. The word “variation” refers to the variety of the types of data. A company could get information from many diverse sources of data, and could be different in the value. The data can be sourced from outside or inside the company. The issue with this is the uniformity and distribution of the information being gathered.
Data collected may be semi-structured, unstructured, or structured in the sense that it is structured. Unstructured data is information that is not organized and comes in a variety of formats or files. Most often, unstructured data are not the best fit to be a common relational database since it doesn’t conform to the traditional data models. Semi-structured data refers to data that isn’t placed in a repository that is specialized however, it does contain information like metadata. This makes it simpler to process as compared to unstructured data. Structured data, for instance, is data that is stored in an organized repository. This means that the data has been better suited to address for efficient analytics and processing.
Veracity
Veracity is the 4th V in the 5 V’s that make up big data. It is a reference to the accuracy and quality of the data. Data collected could be parts that are missing, could be incorrect or not offer an accurate, useful insight. Veracity is the degree of confidence in the data collected.
Sometimes data becomes complex and difficult to understand. A huge amount of information could cause more confusion than information in the event that it’s inaccurate. For instance, in medical fields in the event that information regarding what medications a patient taking isn’t complete, the life of the patient could be at risk.
Both veracity and value determine the quality and insight gleaned from the data.
Value
The last of the 5 V’s of big data is value. This is the benefit that big data has to offer and is directly related to the things that organizations can do with this data. The ability to extract value from large data is essential, since the value of large data can be significantly increased based on the knowledge that can be gleaned from the data.
Companies can utilize the same tools for big data to collect and analyze data, however, how they get value from this data must be distinct to them.
