Big data is a term that describes the large volume of data – both, structured and unstructured – that overloads a business on a day to day basis. But it’s not the amount of data that’s important. It’s what all the organizations do with the data that matters. Big data can be analyzed for insights leading to better decisions and strategic business moves. “Big data” is similar to “small data” but it is bigger in size. Big data is the collection of both structured and unstructured data which are from different sources like social data, machine generated data, and traditional enterprises. There is no single standard definition. According to McKinsey, Big data refers to datasets whose sizes are beyond the ability of typical database software tools to capture, store, manage, and analyse.

Measuring of data
 1024 Bytes = 1 Kilobytes(KB)
1024 Kilobytes = 1 Megabytes(MB)
1024 Megabytes = 1 Gigabytes(MB)
1024 Gigabytes = 1 Terabytes(MB)
1024 Terabytes = 1 Petabytes(MB)
1024 Petabytes = 1 Exabytes(MB)
1024 Exabytes = 1 Zettabytes(MB)
1024 Zettabytes = 1 Yottabytes(MB)
 Characteristics of big data
According to gartner,”big data is high volume, high velocity, and high variety information assets that demand cost effective, innovative forms of information processing for enhanced insight and decision making”.The main 3 V’s are volume, velocity, and variety.
  1. Volume – Volume derives the amount of data from terabytes to petabytes
  2. Velocity – Velocity represents speed the rate of change in the data and how fast it must be processed to gain business value.
  3. Variety – Big data means such more than traditional RDBMS data.It includes unstructured text,sound and movie files,images,documents,geo-location data,web logs etc.
Handling the three V’s helps organisations to extract the big data.The value comes in turning the three V’s into the three I’s,
  1. Informed intuition – predicting likely future occurences and what course of actions is more likely to be successful.
  2. Intelligence – Looking at what is happening now in real time (or) close to real time and determining to take action.
  3. Insight – reviewing what is happened and determing the action to take
 Why big data is necessary?

The convergence across business domains has lead in a new economic system that is redefining relationships among producers, distributors, and consumers or goods and services.Within an organisation, this complexity makes it difficult for business leaders to rely solely on experience (or pure intuition) to make decisions.They need to rely on good data services for their decisions.By placing data at the heart of the business operations to provide access to new insights, organisations will then be able to complete more effectively

Let’s put some numbers together for some of big tech giants

Facebook
  • They stores 300 Petabytes of data.
  • They processes 600 TB of data each day
  • They has 1 Billion user per month
  • They has 2.7 Billion like each day.
  • They has 300 million photographs updated each day.
NSA (National security Agency)
  • They store 5 ExaBytes (10 to power 18)
  •  They process 30 PetaBytes each day
  • They touches 1.6% internet traffic each day.
 Google
  • They store 15 ExaBytes (10 to power 18)
  • They process 100 PetaBytes each day
  • Has 1 Billion unique search user per month
  • They do 2.3 million search in 1 second.

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