IOT and Big Data

 IOT and Big Data

It won’t be wrong to say that the IoT or Internet of Things is leading the paths of becoming the upcoming revolution in the technological world. According to statistics collected by relevant bodies, the amount of revenue generated on account of IoT services and products is expected to exceed more than 300 billion dollars by the end of the year 2020, and that may only be the start of it. Keeping in view the huge sum of data and revenue that the IoT is expected to generate, it is much likely to make waves all across the world of big data thus forcing all the industry to carry out the up gradation of their current processes, tools and the rest of their technology in order to accommodate the huge rise in data volumes. To take a deeper look at the impact of IoT on big data, a few details on the subject are discussed in the paragraphs below.

Data Storage
While talking about Internet of Things, one of the many things that hit our minds is the huge amounts of data that will be hitting the data storages of various companies. All the data centers would need to be highly equipped with the right kind of infrastructure in order to tackle this upcoming dump of data.
As a response to this upcoming need of massive data storage, several different organizations have been thinking about shifting from their own infrastructure of data storage to the PaaS Platform as a Service model. This would need a continuous effort in order to handle the upcoming loads of big data. The PaaS model may be referred to as a cloud based solution that is supposed to offer compliance, flexibility, scalability and one of the most sophisticated architectures for storing valuable Internet of Things data.
Different options of cloud storage include hybrid, public and private models. In case any company has some sensitive data or some other kind of data that may require additional security, a private cloud may prove to be the best choice in this regard. Otherwise a hybrid or a public cloud model may be good enough to serve as a facility to store the IoT data.

Big Data Technologies
When looking to choose the stack of technology to carry out the processing of big data, the massive data influx that is supposed to be delivered by the IoT needs to be kept under consideration. Different companies would require to opt different technologies in order to comply with the IoT data. Disk, network and the compute power would be greatly impacted. So it is important for the companies to devise a solid strategy for taking care of the expected data.
If we take a look at it from the perspective of technology, one of the critically important things is receiving the events from all the devices that are connected to the IoT. All these devices may be interconnected using any technology like Bluetooth or WiFi. Regardless of their means of connectivity, it is important for them to be capable of sending messages to brokers by making use of a well defined protocol. A very popular and widely used protocol in this regard is known as the Message Queue Telemetry Transport MQTT Protocol. Mosquito may be referred to as a very popular broker of MQTT.

Data Security



Different kinds of devices that are supposed to be connected to the Internet of Things and the data that all of them are supposed to be generating is expected to vary greatly in nature. So the entire scenario attracts a lot of risks on account of data security. The heterogeneous world of IoT is comparatively newer to the security professionals currently. So this experience lack also brings about an increase in the security risks. Any kind of attack would not only be threatening to the existing data but it may also cause a good deal of damage to all the connected devices as well.  
So in order for the organizations to secure all their data, they would be needing to deploy some very fundamental changes throughout their entire security landscape. With the evolution of IoT, massive amounts of devices are expected to get connected to the new networks. They would be very different from each other on accounts of sizes and shapes while being capable of carrying out communication with different corporate applications at the same time. Therefore, each of these devices is required to possess a non-repudiable identification in order to prove its authenticity.

A system that comprises of multiple security layers along with accurate network segmentation may prove to be very helpful in the prevention of different kinds of attacks. It may also stop the attackers from getting access to different parts of the entire network. Properly configured Internet of Things systems require following a fine grained policy of network access control in order to figure out which of the IoT devices have authorization to connect. SDN or Software defined networking technologies in collaboration with access policies and network identity may also be used for creating dynamic network segmentation.

Big Data Analytics
IoT and big data may be referred to as the two different sides of the very same coin. Extracting and managing value from all the Internet of Things data is expected to be the biggest challenge that the companies would be facing very soon. Different organizations must do whatever it takes to set up an effective analytics infrastructure or platform for analyzing all the IoT data. They also need to understand and remember the fact that not all of the data they have got on account of IoT is important.
An effective platform for analyzing the data needs to be based upon three different parameters including future growth, infrastructure and having just the right size. As far as performance is concerned, the best solution is to provide single tenant physical servers or bare metal servers to each one of the customers. Hybrid is expected to be the best approach for handling future growth and infrastructure.

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