Computing Sustainable Global Development -Myassignmenthelp.Com

Question: Discuss About The Computing Sustainable Global Development? Answer: Introduction The big data plays a significant role in forming the development of technology and implementing improved technology for the various organizations (Hashem et al., 2015). Big data analytics would comprise of forming the development of the activities of the organization. The big data analytics would help the deep involvement of the operations of the data management. The data management using big data analytics would help the effective modification of the organization (Chen et al., 2015). The IOT devices are helpful for implementing the improved activities so that the business organization would be helpful for forming the effective development. The cloud system analysis would help the business development for increasing the effective and compact development of the data access for the users. The use of the cloud system analysis would help the business development for ensuring that the improved system would be aligned (Jin et al., 2015). The specific modification of the cloud system modifi cation has helped the business organizations for improving their functions and operations and expanding their global reach to customers. The following assignment is deployed for ensuring that the factors of big data challenge for IOT and Cloud network. The report consists of a literature review of the topic for ensuring that necessary and improved information is collected on the topic. The analysis of various literature has helped them in developing the accurate and sufficient operations for the organization. The alignment of the improved functional analysis would also comprise of forming the successive development of the functions. The analysis would provide the option for sorting out the various factors of issues, challenges, and their appropriate solution for the use of big data in the technology of IoT and Cloud network. The report would also comprise of analysis of the advantages and disadvantages of performing the research on the topic of big data issues in IoT and Cloud system. Literature Review on Big Data challenges in IoT and cloud The study of the various literature and articles on Big Data, IoT, and Cloud network has resulted in forming an influential analysis of the topic for forming the general inference on the issues and challenges of the big data in IoT and Cloud system. The Big Data has been influencing the prospect of development of the operations in improved functional development along with enhancing operations (De Francisci Morales et al., 2016). The big data represents the analysis factors for the accountability of the large scale of data usage. The literature review of the big data challenges in IoT and Cloud would be done in the following five sections. Definition of the terms According to Riggins and Wamba (2015), the big data refers to the technology of managing large scale of the data in a single database so that the users can get the benefit of an integrated database. Many large industries had implied the big data technology for ensuring that they can use the technology for globalization. The big companies like Microsoft, Apple, Woolworths, and other global giants have implied the technology for effectively implying the development of the profound system development. The improvement of the improved factors would help in forming the supplementary management of the activities. As discussed by the Srivastava and Chaudhari (2016), the IoT stands for Internet of Things, and it refers to technological instruments that have been helpful for forming the implementation of the advanced technology. The IoT devices and technology would be helpful for forming the successful implication of the effective and improved processing. The use of the IoT devices would allow the users for forming the improved analysis of the operations with the help of IoT devices. The IoT devices are helpful for compiling the development of the technology with the help of effective and improved operations. Sun et al. (2016) have described the cloud computing regarding the technology that forms a virtual database for the users to access and use while ensuring that effective and improved communication is established. The cloud computing system is very helpful for forming the rift in establishing the effective communication in the organization. The cloud network system would allow the modification of the system for developing the improved analysis. Role of Big Data in IoT technology Big data plays a vital role in IoT technology by forming ease of storing the large amount of data that would be required for the framework (Perera et al., 2015). The increase in the volume of data storage would be the primary benefit for the organization by the use of the big data analytics. The supplementary implication of the effective and improved operations would be helpful for forming the supplementary development of the information processing. The big data analytics have helped the organizations to receive the information and store them in a concentric database from the IoT devices. The implementation of the successive development model would help the development of the improved functional analysis. According to Chen et al. (2014), the IoT devices would be connected to other devices using Bluetooth, Wi-Fi, or other means to implement the successive information transfer and access. Role of Big Data in Cloud System The advent of cloud technology was a landmark event for the information system development and storage system (Botta et al., 2014). The cloud system provides a virtual memory to the users so that they can store and access the information whenever required. The Cloud technology had been largely used for effective and improved functional operations. The deployment of the big data information would also help in building the cloud system storage. The Cloud system required big data for forming the effective data analysis. The cloud and big data have been running simultaneously, and it would help in forming the development of improved functions (Hashem et al., 2016). Many global leaders are using cloud computing technology for integrating their operations in the effective and improved operations. Probable Challenges of Big Data in IoT technology The big data technology had been integrated with the IoT technology for easing the implementation and utilization of the information processing (Lee Lee, 2015). It had helped in easing the information processing technology and developing effective operations for the organizations. The probable challenges of using Big Data in IoT technology are helpful for forming the rift in implying effective communication in the organization. The challenges have formed negative impact on the factors like technology, privacy policy, and ethics. According to Tsai, Lai and Vasilakos (2014), the use of big data analytics has resulted in forming the issues related to the storage of the data for IoT devices. The big data storage requires a considerable amount of storage for storing the vast numbers of data. It is probable that the IoT device would require that huge amount of storage for forming the capacity of big data storage. The advent of employing improved data storage would allow the users for forming the consolidated and fixated database. Many IoT devices are compact and it becomes a major issue for deploying the mass storage in the system. For example, the fingerprint identification devices for large-scale industries would require inputting fingerprint and records of hundreds of thousands employees and staffs. However, the device would not be able to store records and fingerprint of so many people altogether. Hence, it would be required for storing the data in a network accessible storage that would be connected to the Io T device. It would give rise to the security concerns for the organization. Ranjan (2017) have stated that the storage of big data is always accompanied by the data security problems. The data security is a major concern for the organizations that store data on big data platform of IoT devices. The IoT devices are connected to the internet cloud network that makes it accessible for the required users. However, the network can also be accessed by external users. The data development is largely responsible for forming the edge of clearing the development model. The slackness of the security would tend to expose the data to unauthorized users also. It would result in the misuse of the existing data by those users for their benefits (Peng et al., 2016). For example- If the database stored in the bill printing machine of a retail store is accessed from outside, then the hacker can access the names of the potential customers, suppliers, and other information of the retail store. Then he/she can use that information for gaining personal benefits by selling it to th e potential buyer (i.e., competitors of the retail store. As explained by Cui, Yu and Yan (2016), the compatibility issue is one of the major factors that have formed the hindrances in deploying the big data in the IoT devices. The big data storage is not present in the IoT devices and it is required for managing the supplementary development of the operations. The compatibility issue arises when the stored data on the big data platform would form the major issues in being used at the IoT devices. The file type compatibility is very crucial for the deployment of the improved functional development (Ning et al., 2015). The compatibility issue would result in making the data void from being used through the IoT devices. The implication of the improved functions would be helpful for forming the successful implication of the operations. The analysis would allow the formation of the improved activities for the modification of the activities. However, the compatibility issues are the major factor for the formation of the improved big data analysis in the IoT devices. Probable Challenges of Big Data in Cloud system The probable challenges of the big data technology in cloud system include the management issue, privacy issue, and replication of the data (Biswas Giaffreda, 2014). The cloud system makes the data accessible to all authorized users. However, the cloud network can also be accessed by external users and it would give rise to the problem of integrity of the data. Moreover, the cloud network can form the issues in integrating the development of the data due to the occurrence of the data duplication. According to Daz, Martn and Rubio (2016), the data management issues arise when the system become incompatible with being managed by the users. The implication of the profound system development would allow the integration of the data in a specific platform. The data management issues are aligned with the development of the operations and it would form the hindrances in developing the operations of the organization. The big data analytics comprises of generating a huge amount of data that must be managed for being used in the IoT devices (Baccarelli et al., 2016). The data management includes entering, storing, modifying, and aligning the activities of the organization for forming the improved operations. The issues of data management had been largely impacting the formation of the operations for the cloud system. The data management in the cloud is largely impacted due to the probability of the issues raised from the large storage. On the other hand, Aazam et al. (2014) have pointed that the data infiltration is a major issue of the big data in cloud system as it results in forming the privacy hindrance for the organizations. The data infiltration is a major factor that forms the rift for the deployment of the effective cloud network. The cloud network results in data infiltration due to the technical security issues. The issues of the network infiltration would develop the formation of the occasional and profound network system (Hansel et al., 2015). The external users would tend to integrate the probability of the data issues in the organization. The data infiltration would result in forming the issues of the data being exposed to external users. The data infiltration would result in forming the integration of the supplementary development model. For example- Online retail stores have been facing some data security infiltrations that have extracted a considerable amount of information regarding clients inform ation and operations. As opined by Cecchinel (2014), the replication of the data is another major issue for the cloud computing system. The replication of the data is caused due to the issues in the implication of the improved functional development. The cloud computing system would be deployed for forming the occasional and supportive deployment of the data processing. The data replication would tend to involve the data redundancy feature of the data processing. The cloud computing system would tend to form the management of the improved analysis and it would involve the completion of the supportive and compact system development (Cai Zhu, 2015). The replication of the data is resulted due to the operational and combinational development. The data replication would result in forming the duplication of the data in the organization and it would consume more memory than required for the organization. For example- the details of the customer can be mistakenly stored in both purchase files and bill receipt f ile of the database unless both of them are integrated into one main database (Sadeghi, Wachsmann Waidner, 2015). The information would again be duplicated in customer details file as well and payment received file. The study by Da Xu et al. (2014), have helped in forming the rigorous analysis of the factors of risk analysis and deploying effective and improved analysis models. The use of the literature and research journals would allow the integration of the various probable issues generated due to the use of Big Data Analytics in the IoT technology and cloud system. The big data development results in forming the analysis of the large scale of information and data. However, it had tended to bring the issues of security, management, and technology for the users. The security issues can be sorted out by analyzing them and forming appropriate solution to the issues of the big data implication for the IoT and cloud system. The integration of the operations of the data would involve the formation of the supplementary development of the activities. The operational development for the organization would allow the formation of the support and development of improved operations for dealing with the pro bability of the occurrence of the issues (Matharu, Upadhyay Chaudhary, (2014). The mitigation strategies would allow the formation of the supplementary development of the operations for fixing the probabilities of the operational development. Issues, Challenges, and Solutions on Big Data challenges The Big Data technology had been helpful for increasing the growth of the operations by forming the improved functions (Firouzi et al., 2018). The technology development had resulted in forming the improvement of the operations and successive system development. The use of big data has been largely helpful for carrying out the successive development of the improved operations. However, the implementation of the activities would tend to result in forming some issues and problems such as need of huge data storage, data security issues, compatibility issue, data management issues, data infiltration, and data replication (Jing et al., 2014). The probability of the issues is dependent on the use of the technology and the effective deployment of the operations. Issues of Big data in IoT and Cloud System The issues of using the big data in IoT devices and cloud system are techno-management based and it has been seen that these issues have impacted the functionality of the device or system resulting in impacting the organization functionally, financially, and technologically. The issues of implementing big data in IoT and cloud system are need of huge data storage, data security issues, compatibility issue, data management issues, data infiltration, and data replication (Al-Fuqaha et al., 2015). The issues have been explained in the following points, Need of huge data storage: The use of big data analytics has resulted in forming the issues related to the storage of the data for IoT devices and cloud system (Bifet, 2016). The big data storage requires a considerable amount of storage for storing the vast numbers of data. Many IoT devices are compact and it becomes a major issue for deploying the mass storage through cloud network in the system. Hence, it is important for ensuring that improved data storage is installed in the organization. The authentic and systematic deployment of the operations would help the business organization for developing the consolidated factor for developing operations. Data security issues: The data security is a major concern for the organizations that store data on big data platform of IoT devices and cloud system. The IoT devices and cloud system are connected to the internet cloud network that makes in accessible for the remote users (Psomakelis et al., 2016). Hence, the external users can also get the probability of accessing the database and extracting information from the database. The slackness of the security would tend to expose the data to unauthorized users also. It would result in the misuse of the existing data by those users for their benefits. Compatibility Issue: The compatibility issue arises when the stored data on the big data platform would form the major issues in being used in the IoT devices and cloud system. The file type compatibility is very crucial for the deployment of the improved functional development. The compatibility issue would result in making the data void from being used through the IoT devices. Data management issues: The data management issues are aligned with the development of the operations and it would form the hindrances in developing the operations of the organization (Conti et al., 2018). The big data analytics comprises of generating a huge amount of data that must be managed for being used in the IoT devices and cloud system. The issues of data management had been largely impacting the formation of the operations for the cloud system. Data infiltration: The data infiltration is a major factor that forms the rift for the deployment of the useful big data for IoT devices and cloud system. The cloud network results in data infiltration due to the technical security issues. The external users would tend to infiltrate the probability of the data issues in the organization. The data infiltration would result in forming the issues of the data being exposed to external users. Data replication: The replication of the data is caused due to the issues in implication of the improved functional development of IoT devices and cloud system. The data replication would tend to involve the data redundancy feature of the data processing. The data replication would result in forming the duplication of the data in the organization and it would consume more memory than required for the organization. Challenges due to the issues of Big Data in IoT and Cloud System The issues of implementing big data in IoT and cloud system are need of huge data storage, data security issues, compatibility issue, data management issues, data infiltration, and data replication. These issues have impacted the functionality of the device or system resulting in impacting the organization functionally, financially, and technologically (Cai et al., 2017). The issues of the big data in IoT and cloud system would have to face the 3V Challenge, Hardware Challenge, Scalability Challenge, Management Challenge, and Skill Requirement Challenge. 3V Challenge: The 3V in big data stands for volume, veracity, and velocity and implication of big data in IoT and cloud system would tend to face these challenges. The big data implication would ease the processing of the data and information (Wang Ranjan, 2015). However, the implication of big data in IoT and cloud system would have to face the problem of amount of data available. The problem arises when a large number of data arrives from a single source or data arrives from some sources. In both the situations, the analysis of the data and derivation of a meaningful outcome from the data would be required. The variable resource of the information and data would tend to form the issues in data storage. The velocity refers to the prospect of the speed of the data receiving from the source (Yaqoob et al., 2017). If the overall incoming pace of the data in very high and higher than that can be managed by the IoT devices and cloud system, then it would raise the challenge of managing the big data. Hardware Challenge: The utilization of the big data for increasing the performance capacity of the operations of IoT devices and cloud system would tend to get issues in implying the successive hardware issues (Cartier et al., 2016). The data warehouses are required for ensuring that improved data analysis and modification is being used. The organizations require the massive data warehouses for propagating the operations of the hardware demonstration model for big data analytics. The hardware data analytics would ensure that the effective and improved operations would be employed. The organization would have to ensure that the improvement of the probable system development would allow the integration of the operations. The hardware challenges would enable the probability of captivating the operations. The organizations have to employ a skilled big data programmer or provide the contract from external (Yang et al., 2017). The organizations would have to employ near real time intervals for the deployment of the improved functions. Scalability Challenge: The scalability challenge of the project is due to the increase of the data for the projects rapidly. The storage of the data would tend to form the possible abrupt increase or decrease of the data flow (Baesens et al., 2016). It would tend to form the operational development in information for managing the data level scaling. The scalability challenge rises when the organization undergoes growth and development. The scalability challenges would tend to form the issues in lateral development of the operations. The organization would have to face the issue of managing the scalable data integration. The help of the scaling of the information would enable the organization for using optimized resources in the big data storage. However, the implication of the scalability is not easy as it would result in forming the increment of the complexity in the organization (Plageras et al., 2017). It requires the usage of largely induced system development in the data managem ent for big data analytics. Management Challenge: The data management issues arise when the system become incompatible with being managed by the users. The data management issues are aligned with the development of the operations and it would form the hindrances in developing the operations of the organization (Li et al., 2016). The big data analytics comprises of generating a huge amount of data that must be managed for being used in the IoT devices and cloud system. The data management includes entering, storing, modifying, and aligning the activities of the organization for forming the improved operations. The issues of data management had been largely impacting the formation of the operations for the cloud system. The data management in cloud is largely impacted due to the probability of the issues raised from the large storage. The management of the big data is a major factor that would impact the processing of the information. Skill Requirement Challenge: The skill requirement challenge for big data implementation in IoT devices and cloud system comprises of requiring skilled workers and technicians (Akhbar et al., 2016). The employment of the operations would converge for realizing the development of the skilled operations. The analysis would provide the development of the system development methods. The integration of the operations would help the business development in forming the accurate and confidential operations. The organizations have to employ a skilled big data programmer or provide the contract from external. Hence it is evident that the employees must have skilled information stored for developing the cohesive and successive information processing. The deployment of the operations would result in forming the operational and improved development model. Probable Solutions of the issues of Big Data in IoT and Cloud System All the issues of big data implementation in IoT devices and cloud system would result in forming the general issues and hindrances in bid data analytics of IoT and cloud system. The probable solutions for the issues and challenges are standard configuration, relational data access methods, and optimization of data processing. These three steps would help in dealing with the issues of security and privacy, data management, data scalability, and data access. Standard Configuration: The use of the standard configuration for the data access would allow the users to the development of the effective and improved functional development (Cortes et al., 2015). The analysis would help the business organization for forming the limited and effective system development functions. The improved functional operations for the data storing and modifying can be done by the standard configuration of the operations. The alignment of the operations would allow the users for forming the system development. The standard configurations of the use of the data storage in the number of compatible operations would be helpful for ensuring that improved functional operations. The configurations would include use of JSON, BSON, and XML formats. These standard configurations would allow the implementation of the supportive development methods. The implication of the standard configuration methods would be helpful for listing the most effective system operations (Peng et al., 2016). The analysis would deploy the modifications of the activities and it would also result in forming the appropriate development. The analysis had helped in forming the modification of the operations and carrying out the development of the improved data modification. Relational Data Access methods: The relational data access methods would be helpful for forming the improvement rift in the operations. The big data implementation for IoT devices and cloud computing would allow the integration of the improved processing and development (Ning et al., 2015). The access to the data would tend to develop the smart access in the organization for the modification of the operations. The use of JDBC/ODBC would be helpful for standardization of the relational data access method. The implication of the relational data access method would help in developing the improved processing and operations. The relational data access methods would be helpful for the modification of the effective and improved operations. The use of the system developed functions would be helpful for modifying the improved functional analysis. The implication of the relational data would allow the implication of the successive development factor. Optimization of data processing: The optimization of the data processing would help in forming the accurate development model for the operations. The data processing for the big data would consume a huge amount of time and functions (Perera et al., 2015). The formation of the operations would allow the integration of the supplementary and actions. The formation of the profound development method would be helpful for forming the modification of the implicit development. The analysis of the development would be helpful for fixing the compact development method. The analysis would be helpful for carrying out the data processing for the organization. The data management using big data analytics would help the effective modification of the organization. The IOT devices are helpful for implementing the improved activities so that the business organization would be helpful for forming the effective development. The cloud system analysis would help the business development for increasing the effective and compact development of the data access for the users (Jin et al., 2015). The use of the cloud system analysis would help the business development for ensuring that the improved system would be aligned. Future Research on topic Big data implication in IoT devices and cloud computing would be helpful for improving the prospects of most of the industries and organization. However, the implication of big data would be more beneficial for healthcare and market study sectors. These two sectors would be largely assisted by the implication of the big data technology. The analysis has also helped in carving the modification of the existing facilities to deploy the improved functional development. Big Data technology in Healthcare industry: Big data has been widely used in most of the commercial sectors and the implementation of the technology in healthcare would provide a massive factor for the development of the improved operations. According to Ranjan (2017), the use of the successive and optimized process would be helpful for carrying out the supplementary development of the improved activities. The organizational processing is helpful for modifying the existing facilities. The implementation of the existing facilities would be helpful for forming the development of the existing technology. The big data would help in easing the process of treatments for the patients. The implication of the big data technology would help the faster data transfer and collaborative modification of the operations. The analysis of the adaptive and cohesive technology for managing the database in the healthcare industry would help in adapting the probability of the improved functional developmen t (Biswas Giaffreda, 2014). The simplification of the operations would be helpful for forming the development of the improved services for the healthcare industry. Big Data Analytics in Market study: The use of big data analytics would be helpful for the studying of the improved functional analysis of the operations (Peng et al., 2016). The market study requires processing of the huge number of data and information. The implication of the proactive formation of the analysis would allow the use of the improved functional analysis. The support and the development of the operations would help the market study analysis for the organizational development factor. The large-scale data and information would help the researchers for analysis of the market trends. The market study would help in improving the economic conditions of the organization. The analysis had also helped in carving out process of the operations. The activities of the operations would be helpful for forming the development of the operations and analysis. Advantages and disadvantages of research The advantages and disadvantages of the operations would be helpful for forming the development of the implication. The advantages of using the research would be helpful for the development improvement of the operations (De Francisci Morales et al., 2016). The initial analysis of the factors of challenges would form the basic information accumulation that would be helpful for forming the mitigation strategies. The use of the technology development would help the organizations for improving the performance and scale of their activities. The big data would help in easing the process of treatments for the patients. The implication of the big data technology would help the faster data transfer and collaborative modification of the operations. The analysis of the adaptive and cohesive technology for managing the database in the healthcare industry would help in adapting the probability of the improved functional development. The simplification of the operations would be helpful for formin g the development of the improved services for the healthcare industry. The implication of the proactive formation of the analysis would allow the use of the improved functional analysis (Lee Lee, 2015). The support and the development of the operations would help the market study analysis for the organizational development factor. The activities of the operations would be helpful for forming the development of the operations and analysis. However, the study would form the exhaustion of resources along with the consumption of time and interest. The main disadvantages of using the big data in operations of varied industries are that the probability of the security flaws would overtake the benefits provided by the system (Perera et al., 2015). The external users would tend to infiltrate the probability of the data issues in the organization. The data infiltration would result in forming the issues of the data being exposed to external users. The slackness of the security would tend to expose the data to unauthorised users also. It would result in the misuse of the existing data by those users for their benefits. Conclusion It can be concluded from the assignment that there are many issues in integrating big data technology with the IoT devices and cloud computing. The study of the various literature and articles on Big Data, IoT and Cloud network has helped in forming the general inference on the issues and challenges of the big data in IoT and Cloud system. Many large industries had implied the big data technology for ensuring that they can use the technology for globalization. The use of big data technology had been integrated with the operations of the technology and its simplified implication model. The support of the developed operations would help the organizations for facilitating the growth and development of the organization. The study had helped in realizing the probable challenges of using Big Data in IoT technology and the probable challenges of the big data technology in cloud system include the management issue, privacy issue, and replication of the data. The cloud system had made the dat a accessible to all authorized users. 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