The 4 V’s of Big Data – In recent years, big data has become a topic of discussion in the IT field that has received worldwide attention. The phenomenon of big data arises from information system methods to be able to cope with the “information explosion” along with current technological developments.
Officially, there is no definition of what is meant by big data, but this term is often used in two phenomena, namely, high speed in accessing large amounts of data, the ability to store, process and analyze data.
Nowadays, the increasingly sophisticated development of the internet gives us the breadth and flexibility to access existing data online, be it data in the form of text, photos, videos, and so on.
Big data is a very large set of data and is now familiar to our ears. Then, do you know what are the characteristics of big data that characterize it? In this article, we will recognize some of the characteristics of big data.
Big data is currently used by most companies which contain information in various forms. Big data can also be used to deal with problems in data to produce data more quickly and effectively.
There are several characteristics of big data, including volume, variety, velocity, and vericity. Some of the explanations below will provide an introduction to the four characteristics of big data.
The 4 V’s of Big Data
The term Big data first appeared in 2000 by an industrial analyst from the West named Doug Laney. In Big Data, data is mixed between structured data and unstructured data. Big data is very large amounts of data that are collected, stored, processed, and analyzed in order to produce useful information to be used as a basis for decision making or policy.
Big data provides benefits after analyzing the data. Examples of the use of various kinds of big data, the benefits of big data can be implemented in agricultural information systems, taxation, health and others.
Below are some of The 4 V’s of Big Data that we will clearly prepare, including:
Velocity (Speed) refers to the speed of data transfer and data compilation. Imagine the speed of credit card validation when we make transactions, or when we open Youtube and play several videos simultaneously, and the speed when we check our cellular credit. Big data technology is able to process and analyze data while it is being used without having to put it in a database.
Data can be accessed at a very fast speed so that it can be directly used in that second (more real time). One of the proofs, among others, is the existence of an online operating system based on Microsoft Silverlight, web-based office applications such as Office365, cloud storage such as Dropbox and GDrive,
Reporting from www.ibmbigdatahub.com, only 10 billion messages have been sent from Facebook and around 350 million new photos have been uploaded every day. This has been going on for more than 10 years.
That’s just from Facebook, please imagine all the videos, photos, emails, or even chats on each of our social networking accounts. This of course requires a very large space that cannot be done by an ordinary computer.
With big data technology now we can store and use data sets with the help of distributed systems. Data can be stored in different places, then connected to the network and unified through applications.
Refers to the amount of big data generated every second. This means a set of data in a very large number and volume and sometimes unstructured. For example Twitter feeds, Instagram feeds, chat text data and Whatsapp status, user click flows from web pages. The flow of these data can be up to thousands of Terrabytes (TB) per second
If you have cloud storage such as Google Drive and Dropbox you can upload any files such as JPEG, MKV, AVI, DOCX, APK, ISO, and so on in one place. Besides that, there is still a need for speed access such as chatting, video calls, sound recorders which have various types of data.
If compiled into a database, it will produce an unstructured database so that access to the file will be slow. With database technology now we can group all types of data into a more structured database.
Data can be called big data if it has various characteristics and is not homogeneous, but has many variables and is very diverse covering various types of data, both structured data in a database and data that is not organized in a database.
Analysis of unstructured data will require slightly different algorithms, such as text, image, sound and video data. For data like that it will take more time to process it, because it could be that in the unstructured data there are other data or new data that can be extracted.
Concerning the validity of a data whether it can be trusted or not. With so many forms of data, the truth about information becomes less controlled, for example in the academic system of a faculty where gender is divided into L (male) and P (female) while in other faculties academic systems use P (male) and W ( woman).
Big data with analysis technology helps us to be able to work with the data through analysis results, because the greater the volume of data, the more inaccurate the data will be. After all the data has gone through these four dimensions, we will get data that has value (Value).
Big data has vulnerabilities in terms of accuracy and validity so it requires depth to analyze big data in order to make the right decisions. The character of veracity refers to how accurate and trustworthy the data is.
5. The 4 V’s of Big Data Value
The value of a data determines the decisions we make after processing all the data. In the business world, it is very important to know the value of data. Without knowing the value of a data, it will be difficult or even wrong for us to take the next step.
Utilization of the right value of data will make a business. become more efficient. Big data is now a necessity for a big business. The Google search engine utilizes big data to make recommendations when we are browsing.
In parts of the transportation business such as O-Jack, big data is used to determine prices and send the closest drivers. In the health sector it is used to predict outbreaks and administer vaccinations.
Big data will continue to grow and continue to be utilized by all sectors. Proper use of big data will provide positive benefits and impacts for every business.
Value means that big data has a very high value if it is processed in an appropriate way or it can also be said how valuable or meaningful a data is. For example, the employee biodata of a company selling food ingredients will not be of value for the purposes of predictive analysis of sales of raw materials to customers.
The data may be insignificant and of no value for one thing, but it can be very important and of great value for another. Data that has no value in any part will not be filtered in the Big data analysis application system.
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Thus the review that Terraveu.com have prepared in full regarding The 4 V’s of Big Data: Volume, Velocity, Variety, Veracity, that’s all and thank you!!