It first glance, both terms might be just pure

It is undeniable that both IoT
and Big Data Analytics are terms that are being used immensely those days and
they are expected to be even more ubiquitous in the near future. At first
glance, both terms might be just pure technical jargons, however Big Data
Analytics proved to be a key game changer in all industries and IoT is no
exception for that. A GFK Eurisko study showed that most organizations are
planning to at least maintain or increase their investment in Big Data
Analytics after looking at its enormous applications and how much this can
affect strategic decisions.

 

IoT is widely defined as “the
worldwide network of interconnected objects uniquely addressable based on
standard communications protocols”.

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Ushering

Cultivating a strong relationship

Prognostications

 

Gartner defined Big Data as “high
volume, high velocity, and/or high variety information assets that require new
forms of processing to enable enhanced decision making, insight discovery and
process optimization” (2012).  Big data comes
in enormous amounts from multiple sources in real-time settings.

 

The number of devices connected
to IoT is expected to reach 75 billion by 2020. In return, this will radically
increase the amount of data generated. Hence, the use of Big Data Analytics to
make sense of these data is becoming more and more inevitable. Big Data Analytics
can enable organizations to better comb into the adoption, usage and impact of IoT.
Although this might be challenging, however it can introduce very promising
value propositions. By scrutinizing these massive amounts of data, a real value
can be created that can benefit individuals, communities and organizations.  

 

IoT businesses can use Big Data
Analytics to accurately anticipate users’ needs and usage patterns allowing
them to tailor their products and solutions to accommodate those needs and
usage trends. Big Data Analytics can add more personal flavor to the impersonal
nature of IoT technologies allowing business owners to dive into users’ mindset
and resolve any riddles. This know-how would drastically lead to more effective
decision-making.

 

What needs to be done to utilize
Big Data analytics more

 

To be able to deploy Big Data
analytics, organizations will need to define clear business objective or need that
they want to accomplish and adapt fact-based decision-making culture.  

The main challenges in IoT
businesses to have effective Big Data Analytics is the need in-house requisite
skills needed to properly deploy and manage big data analytics, in addition to owing
strong data infrastructures and develop the proper analytic tools. Looking
inward for big data expertise did work very well for these organizations. Handing
over this task to Big Data Analytics experts like Simplifico will illuminate
any waste of time, money and effort. Simplifico has profound experience in
working with complex data analytics infrastructures that can leverage IoT data
into meaningful usage patterns and projections. Simplifico can guide IoT
businesses on how to use these data to develop their products and solutions. 

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