To unlock the power of IoT, it requires an intensive understanding of how it can be used to store, manage, process and analyze data.
Smartphones, VR/AR, chatbots, Internet of Things are not just the ways of connecting people and gratifying their personal luxuries but a promise of fine-grained, operational process for businesses and entrepreneurs worldwide. Consumer interest and the plunge into digital economy is excavating with each day passing and each new technology update.
Smartphone apps impact is evident in multiple fields, and data management is not left behind. In fact, for businesses, this whole game is about data.
Startups and enterprises are deriving business value from the smartphone apps and Internet of Things (IoT) because the top reasons to implementing both these technologies are to reduce the operational cost and gain real-time operational control on the common urban environments and within the organizations.
IoT is not easy as it seems. Typically, things may communicate with other things and devices in a room, a home, a car, an office and any open space in an automated environment; for instance, an activity/speed tracker with a smartphone or sensors in, manufacturing units. Having been evolved from the convergence of wireless technologies, micro sensors and the internet, IoT is taking big leaps in data management.
A new deepwater ship may consist of more than 10,000 sensors and can generate over 3 petabytes data daily. This data needs to be scaled, diversified and controlled such that it delivers some value.
Such is the amount of data available when IoT is implemented.
How is the data managed?
In the years to come, the Internet of Things will be bigger than the internet itself and huge volumes of unstructured data will be generated and randomly piled up on the applications. Big data will be a major force driving the IoT in the future.
Because every device you own soon will be connected and thus, a lot of data from each device, each app will be managed across to make things smarter. There will be no fights for AC cooling in workplaces as smart sensor devices will set it to an optimal temperature.
IoT uses machine learning and advanced analytics techniques to deliver data insights that can help company owners and teams to help improve their business efficiency and predict if there are any problems. IoT management will soon be offered as a service.
Companies like Google are providing the right infrastructure and service to process data, with the help of cloud tools including like Google Cloud Machine, Good BigQuery, Google CloudData Flow. Technologies like Qlik, Tableau and Zoomdata are also playing their role sin database management through IoT.
With IoT, only quality data will be actionable data. The information that can create real and meaningful change will only be fetched and processed.
As the Internet of Things is predicted to expand to as much as 20+ billion devices by 2020, which will bring a foreseeable change in the velocity, volume and variety of data.
However, much of the IoT cannot be stored in tables and columns as in relational Database management system (RDBMS), but extremely random data which needs to be channelized and streamlined so that organizations have the flexibility to retrieve and use the data as per their changing requirements. NOSQL Databases like MongoDB and Cassandra will prove to be the best solutions.
In fact, MongoDB is one of the top-performing and ‘first choice of many developers in mobile app development.
Often in real-time scenarios, more power to process and more places to aggregate the data will be required as IoT will connect a number of devices together at one time. So, cloud-based computing platforms are the best solutions to take the surge on new IoT data.
Challenges with IoT
Today, companies relish the concepts of Bring your own device, while they are struggling to do that in a secured manner.
Connecting with IoT is quite challenging as the explosion of things makes it difficult to understand what needs to connect what. The technologies relating to IoT are diverse with the evolution of multiple sensors, software protocols, data formats, and so is the data scattered and unstructured.
Companies are apprehensive of security breaches and data privacy because connection with too many devices may cause loss of data.
Cybersecurity continues to be a threat to rapid IoT adoption. Many IoT devices lack basic security features and thus, are vulnerable to cybercrimes and misuse.
So, for a more strengthened connected between devices, IoT security needs end-to-end encryption, to provide end-users with an amazing technology platform for each and every informationthey require (whether about customer, employee, company’s services and products, customer’s choices and behaviors and about smart living, smart driving and smart working) for performing an operation.
There’s one thing we know for sure: it’s all about a connected world in the future and thus, ignoring the chances to use IoT won’t make it go away. Instead, following the footsteps of technologists and data experts, we, at enterprise level, should find out ways and the right development partner who can help bring forth a solution that’s securely well connected and arrange and process data in the most integrated and coherent manner.
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