There was a time when data was
always discarded because of unavailability of storing space, lacking of
analyzing tools etc. However, Big Data term plays a significant role in today’s
life because almost everything adds on to available data to make it huge for
capturing, storing and analyzing. In exemplification, Facebook generates 10 TB
daily, Twitter generates 7 TB of data daily and IBM claims 90% of today’s
stored data was generated in just the last two years. Due to availability of
data in more than one format and following factors are responsible for the consideration
of Big Data:

Increase in
storage capacities: Nowadays, there are many approaches available for the
storage of Big Data such as Hybrid Cloud Storage which is a combination of
public cloud storage and private cloud storage, where critical data of a
particular organization can be stored in private cloud storage and rest of data
is accessible through distributed public cloud storage. Another possible approach that allows to very large sets of data
is Object Storage. This acts as replacement of the traditional tree-like
file system with a flat data structure in which files are located by unique
IDs, something like the DNS system on the internet.

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Increase in
processing power: Processing power can be increased by adopting
different options like distributed computing which is a model in which different
computers or machines (nodes) are located on networked computers. These
computers communicate and coordinate their actions by passing messages. All the
components interact with each other in order to achieve a single goal.

availability: The data volumes are exploding, more data has been created in
the past two years than the entire history of human race i.e. data is growing
faster than ever before which leads to availability of data in many forms. For
instance – we perform 50,000 search queries every second, which makes 1.2
trillion searches. Besides this, we can see massive growth in video and photo
data, where every minute up to 300 hours of video are uploaded to YouTube

analytical techniques: Machine Learning is an example of advanced analytical
technique which gives computers the ability to learn without being explicitly
programmed. Machine Learning is ideal for exploiting the opportunities hidden
in Big Data. It is well suited to the
complexity of dealing with disparate data sources and the huge variety of
variables and amounts of data involved.

Open –
source software: In these days many open source software are available
to help us sort through Big Data. For example – Apache Hadoop, which is
currently the most popular distributed file processing system. This system is
best known for its ease of use and its ability to process large amount of data
in structured as well as unstructured formats. Its ability of replicating of
data to nodes and making it available on local machine separates it from all
other open – source software.


mentioned factors are the key enablers for the growth of Big Data in today’s