We are entering the Internet of Things, big data analysis and cloud computing era. Each of these technologies has some bottlenecks, such as poor scalability, security issues, installation difficulties, fault tolerance, maintenance, and low performance in traditional information technology frameworks. Therefore, we need to use each of these technologies to find solutions to other problems.
Therefore, the Internet of Things, big data analysis and cloud computing influence each other. Although there is an inherent connection between cloud computing and big data analysis, the Internet of Things plays the role of the data source unit. In addition, breakthroughs in big data analysis and cloud computing technologies will not only solve problems, but will also promote the widespread application of IoT technologies.
We will discuss the interrelationships between the three technologies of the Internet of Things, big data analysis and cloud computing.
Internet of Things, Big Data Analysis and Cloud Computing in a nutshell
Although we are all familiar with the terminology of the Internet of Things, big data analysis and cloud computing, before we discuss the topic, let us outline it −
What is the Internet of Things?
The Internet of Things (IoT) refers to systems that connect physical objects via the Internet. "Things" in the Internet of Things can refer to people or any devices assigned by IP addresses. With the help of embedded technology, "things" can collect and transmit data through the Internet without any manual intervention. It can help them interact with the external environment or internal state to make decisions.
What is big data analysis?
Big data analysis means a large amount of structured, unstructured or semi-structured data (PB or PB), and analyzing these data to obtain insights into business trends.
What is cloud computing?
Cloud computing provides services to users in an on-demand payment model. Cloud providers provide three main services. These services are outlined below:
1) Infrastructure as a Service (IAAS)
The cloud service provider provides the entire infrastructure and maintenance-related tasks.
2) Platform as a Service (PAAS)
Cloud providers provide resources such as object storage, runtime, queues, and databases. However, the responsibility for tasks related to configuration and implementation rests with the user.
3) Software as a service (SAAS)
If the IaaS of the platform and infrastructure is in place, this service is the most convenient service, which provides all the necessary settings and infrastructure.
The relationship between big data analysis and cloud computing
With the generation of large amounts of data, cloud computing plays an important role in the storage and management of that data. This involves not only the growth of big data analysis, but also the expansion of data analysis platforms such as Hadoop. As a result, it has created new opportunities for cloud computing. Therefore, service providers such as AWS, Google, and Microsoft are providing their own big data analysis systems in a cost-effective manner that can be scaled for enterprises of all sizes.
In turn, this has led to a new service model called "Service as Analysis (AaaS)". This will provide a faster and extensible way to integrate different types of structured, semi-structured and unstructured data, analyze it, transform and visualize it in real time.
In addition, the big data analysis cloud computing relationship can be evaluated from the following viewpoints and benefits:
Cloud computing environments usually have multiple user terminals and service providers. Users use big data analysis tools to collect data from the collection terminal. On the other hand, it saves, stores and processes big data analysis from the service provider side. Therefore, cloud computing provides a big data analysis infrastructure. The infrastructure must provide on-demand resources and services to ensure uninterrupted services.
Because the cloud environment is scalable, it can provide appropriate data management solutions regardless of the amount of data. If necessary, cloud computing service providers can also provide security policies based on user requirements.
Identity management and access control are the two main issues when handling company confidential data. By abstracting the internal details of information, cloud computing can use a simple software interface to meet this security requirement. In addition, this guarantees the complete confidentiality of user data and only provides access to authorized users.
Big data analysis for data processing can be distributed all over the world, and maintaining such a large server in different locations is an expensive measure for organizations. Because cloud computing can store and process data through geographically dispersed servers and virtual servers, the cost of big data analysis and processing is greatly reduced.
Cloud computing uses advanced software and applications that do not depend on the efficiency of user equipment. In addition, it depends on the network server and its strength. On the contrary, if we use personal resources for big data analysis that depends on user equipment. Therefore, big data analysis cloud computing services are beneficial.
Cloud computing supports high-speed data flow through the network. As a result, it leads to faster big data analysis and processing.
The relationship between IoT and big data analysis
The Internet of Things is an opportunity to simplify the operations of many departments to realize the interaction between machines and people (M2H) and equipment and machines (M2M). So far, it has enough room for improvement. In most cases, the data generated by the sensor is fed to a big data analysis system for analysis and a final report is generated from it. Therefore, this is the main point of the interconnection between the two technologies.
The intersection of IoT and big data analytics brings new IT challenges
1) Data storage
2) Integration
3) and analysis
However, it creates many opportunities, not challenges. The Internet of Things is expected to bring a market potential of US$19 trillion to the Internet industry in the next ten years, which will provide more opportunities for research and development in the field of Internet of Things and big data analysis.
The relationship between the Internet of Things and cloud computing
The Internet of Things has developed a new concept of Internet networks. This allows communication between multiple objects, including
1) Smart devices
2) Mobile devices
3) Sensors and others.
The architecture of the Internet of Things provides effective communication between all elements of the architecture. Element may be
1) Object
2) Gates
3) Network infrastructure
4) Cloud infrastructure
There are multiple benefits of combining the Internet of Things and cloud computing:
1) In the cloud infrastructure, you can deploy applications to quickly process and analyze data, and make decisions as quickly as possible.
2) It is estimated that by 2020, nearly 4.4 trillion GB of data will be generated. This will undoubtedly put tremendous pressure on its infrastructure. Therefore, it is necessary to minimize this huge pressure and find a solution to transfer data. On the other hand, cloud computing can provide sufficient performance and scalability to store and manipulate such a large amount of data.
3) The Internet of Things and cloud computing have a complementary relationship. When the Internet of Things generates large amounts of data, many cloud providers allow data to be transmitted over the Internet, which means that it provides a way to navigate the data.
4) Cloud computing facilitates collaboration in the development of the Internet of Things. Using the cloud platform, IoT developers can store data remotely and easily access it.
5) Cloud computing helps advance the analysis and monitoring of IoT devices.
6) Once any security breach occurs in the infrastructure, IoT devices using common APIs and back-end infrastructure can immediately receive important security updates through the Cloud. The combined function of the Internet of Things and cloud computing is an important parameter to ensure user safety and privacy.
Ultimately, it is the integration of the Internet of Things, big data analysis and cloud computing
Therefore, from the above description, we can find the interdependence between the three mutually exclusive technologies. Here, cloud computing plays the role of a common workplace for the Internet of Things and big data analysis, where the Internet of Things is the source of data, and big data analysis as a technology is a data analysis platform.
According to IDC, in the next five years, more than 90% of IoT data will be hosted on cloud platforms. The reasons behind it are:
1) A large amount of IoT data generation will provide data for the big data analysis system.
2) Reducing the complexity of data mixing in the Internet of Things is one of the criteria to maximize its benefits. The concept behind it is-if IoT applications and data islands operate, we will not be able to reach their full potential. Therefore, in order to gain better insights and make decisions, mixing information (data) from various sources is the best way.
Therefore, for the above two points, we clearly believe that a cloud-based system is needed for the Internet of Things and big data analysis. This shifted from product orientation to information-based result orientation.
Bottom line
All in all, the integration of the Internet of Things, big data analysis and cloud computing takes advantage of the new vision of decision support systems. In addition, the integration of the Internet of Things, big data analysis and cloud computing can provide new opportunities and applications for all industries. For professionals who are currently researching individual technologies, this will also provide them with an excellent career scope.
At Whizlabs, we use knowledge in the fields of IoT, big data analysis and cloud computing, as well as market-leading certification guides that will help professionals gain theoretical and practical knowledge. The certification guide has been carefully designed to ensure success in the actual exam.
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