The term “big data” has been broadly becoming a buzz word – combination of both technical and marketing. Edd Dumbill, principal analyst for O’Reilly Radar in simple terms defined it a Big data is data that becomes large enough that it cannot be processed using conventional methods. The size of the data which can be considered to be Big Data is a constantly varying factor and newer tools are continuously being developed to handle this “Big Data”.

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What is Big Data and its Characteristics?
Did you know that 90% of the data in the world today was created in the last two years? The
growth of data will continue to rise as the cost of storage decreases. Below is the rate of growth
of data since 2005 to 2015(forecast) – IDC Research
What is Big Data?
The term “big data” has been broadly becoming a buzz word – combination of both technical
and marketing. Edd Dumbill, principal analyst for O’Reilly Radar in simple terms defined it a
Big data is data that becomes large enough that it cannot be processed using conventional
methods. The size of the data which can be considered to be Big Data is a constantly varying
factor and newer tools are continuously being developed to handle this “Big Data”.
How much data is Big Data and how fast is it growing?
To put some historical context and evolution of systems and technology – we must understand
the best use of technology is where you are solving a problem or pain point. For example, Keg
Kruger, Bixo Labs in his presentation – A Very Short History of Big Data” described how the
US census used Hollerith Tabulating Systems in 1890 to tabulate millions of pages of data
which was historically being done manually. Hollerith’s tabulating company with three other

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companies were combined to form Computing Tabulating Recording Corporation which is now
International Business Machines – IBM.
We must first understand, how do we measure of data? Byte (8 bits equals 1 byte) is a unit of
measure of digital information. it is important to understand the below metrics as we start
looking at big data. Big Data is certainly not a measurement but we should understand how
much data is considered “Big”. In the table below – the starting of terrabyte of data is
considered to starting of what is referred to as big data.
Definitions Estimations
Gigabyte:1024
megabytes
4.7 Gigabytes: A single DVD
Terabyte:1024
gigabytes
1 Terabyte: About two years worth of non-stop MP3s. (Assumes one
megabyte per minute of music)
10 Terabytes: The printed collection of the U.S. Library of Congress
Petabyte:1024
terabytes
1 Petabyte: The amount of data stored on a stack of CDs about 2 miles
high or 13 years of HD-TV video
20 Petabytes: The storage capacity of all hard disk drives created in 1995
Exabyte:1024
petabytes
1 Exabyte: One billion gigabytes
5 Exabytes: All words ever spoken by mankind
Source: IBM
What are the characteristics of Big Data?

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Big Data can be described by the following characteristics:
(i) Volume – The quantity of data that is generated is very important in this context.It is the
size of the data which determines the value and potential of the data under consideration and
whether it can actually be considered as Big Data or not.The name ‘Big Data’ itself contains a
term which is related to size and hence the characteristic.
(ii) Variety- The next aspect of Big Data is its variety.This means that the category to which Big
Data belongs to is also a very essential fact that needs to be known by the data analysts.This
helps the people, who are closely analyzing the data and are associated with it, to effectively use
the data to their advantage and thus upholding the importance of the Big Data.
(iii) Velocity- The term ‘velocity’ in this context refers to the speed of generation of data or how
fast the data is generated and processed to meet the demands and the challenges which lie
ahead in the path of growth and development.
(iv) Variability- This is a factor which can be a problem for those who are analyse the data. This
refers to the inconsistency which can be shown by the data at times, thus hampering the
process of being able to handle and manage the data effectively.
(v) Complexity- Data management can become a very complex process,especially when large
volumes of data come from multiple sources.These data need to be linked,connected and
correlated in order to be able to grasp the information that is supposed to be conveyed by these
data.This situation,is therefore,termed as the ‘complexity’ of Big Data.
Examples of Big Data
Data comes mainly in two forms-
1. Structured, and
2. Unstructured Data (there are also semi-structured data – eg. XML)
Structured data has semantic meaning attached to it whereas Unstructured data has no latent
meaning. The growth in data that we are referring is most unstructured data. Below are few
examples of unstructured data -

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1. Calls, text, tweet, net surf, browse through various websites each day and exchange
messages via several means.
2. Social media usage my several million people for exchanging data in various forms
also forms a part of Big Data.
3. Transactions made through card for various payment issues in large numbers every
second across the world also constitutes the Big Data.
Hope this posts gave you enough of infomation about Big Data and in future posts, we will be
looking at – Applications of Big Data i.e. Big Data Analytics, Careers in Big Data – From
Software Engineer to becoming a Data Scientist, Hadoop and Applications.
Big data Analytics Course in Bangalore