What are characteristics of Big Data?

Big Data characteristics is a pure term that describes the incredible value of Big Data. This software engineering is strictly build to handle the enormous data that is generated every second. Let us check out some key characteristics of Big Data in this article. You can also know the advantages and disadvantages of Big Data to know more about it.

Points on characteristics of Big Data:

  • Volume (Size of Data)

Volume is the size of the Data that is actually stored and generated. Depending on the size of the data, the data set is large or not.

Volume refers to the incredible amount of information produced every second from social media, cell phones, vehicles, credit cards, M2 M sensors, photos, videos, and everything else. We are now using distributed systems to store data at a variety of locations and to put together a platform program such as Hadoop.

Attribute: Zettabyte, Yottabyte, Exabyte

Example: We create 2.5 quintillion bytes of data every day.

  • Variety (Types of data and source)

Variety refers to the nature, structure, and type of data that is being used.  It defines different types of data and data resources. Big Data is generated in several varieties, as discussed earlier. Contrary to conventional data such as phone numbers and addresses, the new data phenomenon is in the form of images, videos, and audios and much more, making about 80% of the data entirely unstructured. Structured data is just the tip of the iceberg.

Attribute: Degree of structure, Complexity

Example: Mobile, Social Media, Video, IoT

  • Velocity (Speed of data in and out, generated)

Compared to the others, velocity plays a major role. There is no point in investing too much to end up waiting for the data. So, the major aspect of Big Data is to provide data on demand and at a faster speed. This represents the motion of the data. It has changed the mindset of yesterday’s data. The flow of data is now almost real-time, and the update duration has been reduced to a fraction of a second.

Attribute: Streams, Batch, Near/Real-time

Example: Every 60 seconds 400-hour new youtube vide share, 2430555 Instagram Likes.

  • Veracity (Usefulness and Accuracy of data)

Veracity basically means the degree of reliability that the data have to offer. Since a large part of the data is unstructured and irrelevant, Big Data needs to find an alternative way of filtering or translating it, as data is crucial to business development.

Attribute: Completeness, Consistency, Integrity, Ambiguity

Example: Insight the available data accurately

  • Value

Value is the major thing that we need to concentrate on. It is not about the quantity of data we store or process. It is actually the amount of valuable, reliable, and trustworthy data that needs to be processed, analyzed, and stored to find insights. Our ability and needs to turn data into value. So, value is profit, medical or social benefits, customer/employee, or personal satisfaction.

Apart from this, the researcher comes up with some additional characteristics such as variability, validity, and volatility.

 

Explore more information:

  1. Advantages and disadvantages of Big Data
  2. What are the use and need for Big Data?
  3. Benefits of using Big Data in the manufacturing industry
  4. What are the advantages of Big Data in accounting?
  5. What are the risks and challenges of Big Data?
  6. Challenges of Big Data in healthcare

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