The Internet of Things(IoT) is gradually leading us to interact with “things”. The large amounts of
data that many smart devices are going to produce is used to make this happen,
and that is going to change the way Big Data is handled. Let us understand how.
Big Data Storage
How much data that will
be generated is the first thing appearing when the adoption of IoT keeps
increasing. Multiple channels are used to keep such large amounts of data. To
create a flexible and scalable method to handle IoT data, Big Data
organizations are prepping up to move to the PaaS (Platform as a Service)
model.
Big Data Security
It is important to
increase security when increasing data. IoT will create a network of varied
devices that will also lead to a pooling of varied types of data. IoT Data
Security will be a new challenge put across with Big Data Security
professionals. If any security loophole happens, the entire network of connected
devices will be put at risk of manipulation.
The verification and
authentication of devices that are added to the IoT network will become vital.
It will become the task of Big Data organizations to create a checkpoint to
audit the devices that are added to the network.
Big Data Technologies
IoT is supposed to
connect devices over Wi-Fi and Bluetooth. The data passing between the devices
will also be sent over these channels and there must be leak-proof technologies
implemented to capture this immense amount of data. Protocols must be put in
place to offer a controlled mechanism of data receiving and storing. Mosquitto
is a very popular protocol and adaption of Hadoop to store the data generated
by IoT networks is also in process.
Big Data Analytics
IoT and Big Data are
interconnected with each other. IoT is going to generate huge amounts of data
that must be analyzed if the IoT networks are going to operate accurately. The
networks may generate some redundant data and that is why it becomes important
for Big Data organizations to spend their analytics power on the data that is
important. So, a new element of data categorization will be added so that the
Big Data Analytics tools deliver better performance.
Conclusion
Big Data organizations are
going to receive a huge amount of data for analysis by IoT devices. At the
moment, Big Data companies are only just becoming capable of handling this
immense amount of data in a highly secure manner. The change we are expecting
on the Big Data front would be the adoption of flexible and scalable solutions
to enhance security, data storing, and data analysis capabilities.
IoT is still new for many
people. The wider IoT’s adoption is, the more important that Big Data
organizations must prepare to handle various type of data sending from
different types of IoT devices.
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