In today’s digital world, data is everywhere, and almost every individual, company, the organization is running through data and big data techniques. Have you ever thought of driverless cars, today’s advanced voice assistants (Alexa& Siri), many world records that can be found in a few clicks? These all are possible with big data tools and techniques that are making our lives and business world a better living space. Organizations using big data can improve their operations, provide better customer services, create and implement personalized marketing campaigns and can take other crucial actions that help increase profits and revenues. With big data analytics, companies can harness their data and use it to search and gain new opportunities.
Big Data is becoming crucial as it allows organizations to work with their data efficiently and make better real-time data-driven decisions. It is witnessed that several social apps are being developed, which result in increasing data massively every day, and this huge amount of data is handled, processed, and stored through big data tools and techniques. Here the importance of Big Data comes to light. This is the reason there is a high demand for skilled big data experts along with training courses such as Big data online courses, to fill the gap between the demand and supply.
Here we are going to discuss the five Vs of Big data.
What Is Big Data?
Big data is the collection of a huge volume of data that is growing exponentially with time. Big data is always large in volume and complex, which is difficult to process using traditional methods. It is basically a collection of structured and unstructured data sets that inundate businesses on a day-to-day basis. But these massive volumes of data can be used to identify business problems that wouldn’t have been able to manage before. Big data can be analyzed for meaningful insights that can improve the decision-making process and provide confidence for making strategic business moves.
In other words, Big data refers to data that contains greater variety, arriving and increasing columns and with more velocity. Today, Big data has become an important capital for almost every organization that can offer a large part of the value. Here data analysis is the process by which data analysts can find data value that can offer various benefits such as insights, trends, and more. So here we can better understand Big Data with its five Vs.
Five Vs of Big Data
There are five important Vs that can define big data better and properly: Volume, Velocity, Variety, Value, and Veracity. Let’s understand each V better with the following mentioned description.
- Volume- The first V that describes Big data is its huge Volume. Volume is considered the base of big data. Data gathered from a variety of sources that involves transactions, videos, images, industrial equipment, smart devices, social media platforms, and more is known as the volume or amount of big data that matters. Here data can be of unknown value like Twitter data feeds, clickstreams on a mobile app or a web page, or sensor-enabled types of equipment. Here the main work of big data is to process high volumes of low-density, unstructured data that can be so huge that might be tens of terabytes of data and for others, it can be hundreds of petabytes. The volume of Big data can be relative, though, and can change depending on the available computing power that’s on the market.
- Velocity- After volume second important V of big data is its velocity. It refers to the high speed of accumulation of data. Velocity is all about how quickly data is generated and how quickly that data moves. It is a crucial requirement for organizations to flow their data quickly and be available at the right times to make the best business decisions possible. We know that there is an enormous and continuous flow of data here velocity determines the potential of data and how fast the data is generated and processed to meet the demands where data flows from several different sources like social media, machine networks, mobile phones, etc.
- Variety- Next important V for Big data is its variety that completely refers to the nature of data whether it is structured, unstructured, or semi-structured. It is also referred to as heterogeneous sources and diversity of data types. Variety depends on the arrival of data from many sources that can be both inside and outside of an enterprise. Here it is all about standardization and distribution of all data being collected. Variety of data is Structured (organized data refers to data that has defined the format and length of data), Semi-Structured (semi-organized data that do not conform to the formal structure of data), and Unstructured (unorganized data, which refers to data that don’t fit neatly into the traditional column and row structure of the relational database).
- Veracity- It is the fourth V of big data that refers to the accuracy and quality of data. Companies that receive data could have missing pieces, inaccurate, or may not be able to give real and meaningful insights. So here Veracity is the level of trust and accuracy in the collected data. It can define inconsistencies and uncertainty in data. We know that Big data is variable so data in a huge quantity can create confusion and on the other side less amount of data could not convey the complete information. So both veracity and value can define the quality and insights collected from data.
- Value- Now here is the 5th V of Big data – Value. It is all about finding valuable information in data as the bulk of data having no value is of no good to the company, unless you turn it into something useful. Big data can convert the data into something valuable to fing meaningful insights and information and here comes the importance of Value and you can state that Value, is the most important V of all the five Vs.
Now that you are familiar with the five Vs of big data, why not enroll in a big data training course and learn the other concepts covered in this field!
