Big Data Characteristics are simply words that describe Big Data’s incredible potential. This pinnacle of Software Engineering is solely built to handle the massive amounts of data generated every second. In this blog, we tell you about the top 5 Vs of Big Data.
Big Data refers to massive amounts of data that cannot be stored or processed by typical data storage or processing equipment. Big Data is generated on a massive scale, and it is being processed and analyzed by many global corporations in order to reveal insights and improve the business of numerous organizations.
Various Types of Big Data
Big Data is broadly classified into three types. They are as follows:
- Data Structured
- Semi-Structured Information
- Data that is unstructured
Structured data has a dedicated data model, a well-defined structure, a consistent order, and is structured in such a way that a person or a computer can simply access and use it. Structured data is typically stored in well-defined columns as well as databases. Database Management Systems are an example (DBMS)
Structured Data can also be classified as semi-structured data. It shares a few qualities with Structured Data, however, the majority of this type of data lacks a specific structure and does not adhere to the formal structure of data models such as an RDBMS.
Unstructured data is a completely separate type of data that does not have a structure and does not adhere to the formal structural rules of data models. It does not even have a regular format and is constantly changing. However, it is unusual that it contains data and time-related information.
Audio files, images, and so on are examples.
Volume
Volume refers to the enormous volumes of data generated every second by social media, cell phones, autos, credit cards, M2M sensors, photos, video, and other devices. Facebook alone may generate billions of messages, 4.5 billion “like” button clicks, and over 350 million new postings are submitted every day. Only Big Data Technologies can handle such massive amounts of data.
Veracity
The degree of reliability provided by the data is referred to as its veracity. Because a large portion of the data is unstructured and unimportant, Big Data must devise an alternative method of filtering or translating it, as the data is critical in company advancements.
Value
The main problem that we need to focus on is value. It is not only the amount of data that we keep or process that is important. It is the amount of valuable, dependable, and trustworthy data that must be saved, processed, and evaluated in order to gain insights.
Variety
As previously discussed, Big Data comes in a variety of forms. In comparison to traditional data such as phone numbers and addresses, the latest trend in data is in the form of images, videos, audios, and many more, resulting in around 80% of the data being fully unstructured. The use of structured data is only the tip of the iceberg.
Big Data Technology is widely used in the financial and banking sectors. Big data analytics can help banks understand client behaviour based on inputs such as investment patterns, shopping trends, investment motivation, and personal or financial backgrounds.
Big Data has already begun to make a significant influence in the healthcare sector. Medical professionals and Health Care Personnel are now able to give individualized healthcare services to specific patients thanks to predictive analytics.
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