Big data meaning:
Technology has revolutionized our way of living. It is being used in every aspect of life. As we are using smartphones, social media accounts, and much more. We generate data in huge amounts. This data is known as big data and its types are carried out.
As research, 2.5 quintillion bytes of data generated through smartphones, social networks, and the internet of things. All around the world, these big data sources are available.
Keep reading this to know more about big data and its types.
What is big data technology?
Big data is defined as a huge collection of data that is growing at a fast rate. This data cannot be processed by traditional storage or processing units. For its processing, it requires advanced technology.
Its significance lies in the patterns and insights that can drive business decisions. Because when big data is extracted by using advanced analytical technologies. Then these insights assist organizations to understand how their users, market, society and the world behaves.
Example of Big data:
The New York Stock Exchange is an example of big data that generates one terabyte of new trade data per day. The statistic shows that 500+ terabytes of new data get ingested into databases of social media. Like Facebook, Instagram, and many others. It’s produced by pictures and video uploads, comments, and much more.
How big data works
5V’s of Big Data:
HDFS architecture and components
- Volume Velocity
The size of data plays an important role in determining its value out of data. Volume is a characteristic that should be considered for data. It tells whether data is big data or not. This requires hyper-scale computing environments with large storage and fast IOPS (input/output operations per second).
This term means the speed of the generation of data and how it’s produced and processed to meet the demands. Also to determine the real potential in the data. It deals with the speed at which data flows in from sources like application logs, social media sites, smartphones, and others.
Big data collected from various sources and variability occurs in it. The flow of data is massive and continuous. These days the data comes in an array of forms PDFs, Audio, SM photos, emails, and others. So, they must be processed into structured databases for data analytics also decision-making.
This term means how much data is reliable. When data is updated in real time, unreliable data devalues the authenticity of big data. So, data authenticity requires regular checks during collection and processing. That’s why the quality and reliability of data are a big concern.
Value is an essential characteristic of big data. Any type of data is not important if it’s not valuable. So, value is consider in the collection and processing of data. Big data should be valuable and reliable that we analyze, process and store.
Big data tools Its Types:
There are three types of big data into which it is classified.
Any data that can be processed, accessed, and stored in a fixed format is called structured data. When you are dealing with big data. Then the structured data is the best to work with. Because it is a measurement that is defined by setting parameters.
Address, Age, Billing, Credit/debit card numbers, and others.
This refers to big data that lacks specific structure is known as unstructured data. It makes it very difficult to process and analyze. It poses many challenges in terms of processing for deriving value out of it. Mostly, this data is in raw format or unstructured form.
Email, the output returned by ‘Google Search’ etc.
Semi-structured data contains both forms of data. It means that it has structured data and unstructured data as well. In format, it’s structure but it is not defined properly. This type of big data is not ordered under a particular database.
In this big world, big data exists in huge amounts. They are classified into three different types. This has many benefits like improved customer service, better decision making, better operational efficiency, and much more.