SERIES 2
The big data stands on mainly 5 pillars are Volume, Velocity, Variety, Veracity and Value.These pillars are briefly describes in 3 V’s and 5 V’s architectures.
Shubham Rajput · Follow
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“Accurate and required data which having great values with real time information, it contributes in right decision making.”
- Shubham B. Rajput
Definition:
Big Data is the huge amount of data which includes various types of data captured, generated or shared through streams or any transmission way which is able to process in real time.
-Shubham Rajput
Concept:
Big data is simply the all data exist in this world for example someone posted a video on Facebook, someone posting an image/photo, someone is briefing on internet, someone is chatting with his/her favorite one or even this text that you see or hear now directly or indirectly. By processing on big data we can predict the behavior of result about particular thing.
Recently, we study the definition and concept of big data. Now, question is “How to identify Big Data?” To explore answer for this question refer following paragraphs.
The characteristics of Big Data are categorized in various types of V’s concepts. The main types of V’s are 3 V’s and 5 V’s which demonstrated the pillars of Big Data in brief. In order to identify big data it is necessary to acquire following characteristics. It is very efficient way to understand actually “What is Big Data” and “How can identify it?”.
“The big data stands on mainly 5 pillars are Volume, Velocity, Variety, Veracity and Value.These pillars are briefly describes in 3 V’s and 5 V’s architectures.”
Following paragraphs demonstrates 3 V’s and 5 V’s:
3 V’s:
3 V’s contains 3 main characteristics of Big Data. These characteristics are Volume, Velocity and Variety. Each keyword are self explanatory. Each *characteristics demonstrate separate physical as well as logical attributes.
1) Volume:
i. In big data, Volume is the huge set of data which has huge form.
ii. The volume describes the huge set of data which is very complex to process further for extracting valuable information from it.
iii. Volume does not describe actual size to grant it as big data, it have relatively big size. The size could be in Terabyte, Exabyte or even in Zettabyte.
iv. The size of big data makes perplex it to process.
Data Measurement Rows:
1. Bit is an eighth of a byte
2. Byte: 1 Byte
3. Kilobyte: 1 thousand or, 1,000 bytes
4 .Megabyte: 1 million, or 1,000,000 bytes
5 .Gigabyte: 1 billion, or 1,000,000,000 bytes
6. Terabyte: 1 trillion, or 1,000,000,000,0000 bytes
7. Petabye: 1 quadrillion, or 1,000,000,000,000,000 bytes
8. Exabyte: 1 quintillion, or 1,000,000,000,000,000,000 bytes
9. Zettabyte: one sextillion or 1,000,000,000,000,000,000,000
10. Yottabyte: 1 septillion, or 1,000,000,000,000,000,000,000,000 bytes
For Example : The world generates 2.5 Quintillion bytes of data per day.
2) Velocity:
i. In big data, Velocity demonstrate two things mainly,
(1) Speed of growth of data (2) Speed of transmission of data
ii. Velocity refers to data generating, increasing and sharing at a particular speed through the resources.
iii. Speed of growth of data:
The data increases day by day through various resources. Some of the resources are explained below,
Internet Of Things (IOT): IOT is prominent for contributing in big data. It generates data through IOT devices placed in automated vehicles, digital IOT bulbs, IOT based robots etc.
Social Media: As you see, users on social media increasing day by day so that they exactly generating huge batches of data.
Such as many other resources, who generates data at such high speeds.
iv. Speed of transmission of data:
The speed is also take major role in identifying big data.
Big data increasing in rapid fast manner which makes it very complex to process fast and makes difficult to transmit it quickly through fiber optic or electromagnetic way of transmission.
Therefore this term is very important to demonstrate velocity.
For Example : Twitter generates 500 Million tweets per day, rate of speed of generation of data and rate of speed of transmission of data is very high.
3) Variety:
i. In big data, Variety is nothing but different types of data.
ii. This term demonstrate various types of data such as texts, audios, videos, XML file, data in rows and columns etc.
iii. Each type of data have separate way to process itself therefore, it is necessary to categorize different types of data.
iv. In Big Data, data is categorize in mainly three types as follows,
a. Structured Data: The data which is in the format of relational database and have structured properly in rows and columns format is known as Structured Data.
b. Unstructured Data: The data which includes various types of data such as audio, video, XML file, word file etc. and does not organize in proper format then it is said to be Unstructured Data.
c. Semi-structured Data: Semi-structured data is self-explanatory that it is the data which not fully structured or unstructured. In it, data is partially structured and mixed with unstructured format of data.
For Example: The social media contains photos, videos and texts of people in huge figure. This data is nothing but big data, it can be well-structured or unstructured or semi-structured.
The concept of 3 V’s explains the basic architecture of big data but 5 V’s fulfill some more requirements to make it well demonstrated. Following paragraph explain architecture of 5 V’s concept.
5 V’s:
5 V’s contains Volume, Velocity, Variety, Variability and Value. Therefore, simply the concept of 5 V’s is “5 V’s = 3 V’s + Veracity + Value”. The Veracity and Value are described as follows:
4) Veracity:
i. Veracity is the accuracy, meaningfulness and confirmation of true data.
ii. It is very difficult to extract correct information/data from the huge set of various types of data.
iii. Veracity is very important term in processing of big data because, any inaccurate, fake and meaningless data leads to damage in revenue or required results.
iv. Therefore it is necessary to extract real data from big data.
For Example: The outdated data on social media, doesn’t going to predict for future results, therefore it is very necessary for data to having property of veracity.
5) Value:
i. The most important pillar of Big Data is Value.
ii. If data exist without value means if an extracted data not leads to get valuable information from itself, then it surely doesn’t exist in category of big data.
iii. Accurate and required data having great values, contributes in right decisions.
For Example: If data is real time, accurate and meets requirements of customer’s correct result prediction, then it generates higher cost for customer to predict.
There are more V’s demonstrated for Big Data but, 3 V’s and 5 V’s concept describes it in brief as well. Therefore, in this chapter we studied architecture of big data using 3 V’s and 5 V’s concepts.
Conclusion:
- By studying this we got answer of question “How can identify Big Data?” using 3 V’s and 5 V’s concept.
- The big data stands on mainly 5 pillars are Volume, Velocity, Variety, Veracity and Value.These pillars are briefly describes in 3 V’s and 5 V’s architectures.
Writer: Shubham B. Rajput
Linkedin: www.linkedin.com/in/shubhamrajput0369
