To what extent is the use of big data management in cloud computing a positive development in organisations?
Big data can be classified as a large set of data that is high in volume, velocity and variety . volume refers to high amount of data, velocity defines the speed of incoming and outgoing data and variety means range of data sources from where data is coming. Data can be in structured, semi-structured or in raw format (De Mauro , Greco & Grimaldi , 2015).
Approximately about 2.5 quintillion byte of data is generated on a daily basis from various digital sources which contributes to the 90 percent of the world data generated till date (Daas et al . , 2015). According to the article, popular social media site Facebook make use of big data to process 50 billion photos from the user database daily and Wal-Mart handles more than 1 million data related to customer transactions every hour which is equivalent to 2.5 petabytes of data.
Cloud computing is the most prefered technology adopted by various industries for big data management. It is not only capable of processing large amount of data both in structured and unstructured form, it also make data base more secure and efficient which is one of the major factors for the popularity of the technology in the recent market (Hasem et al . , 2015)
Cloud computing refers to outsourcing of computer resources over the internet to the users whenever they requires it (Fehling et al . , 2014).
Three advantages of cloud computing is discussed bellow along with the drawbacks.
With big amount of data comes even bigger challenge to make that information secured and intact. Cloud computing has an important role to play in this context (Rittinghouse , W & Ransome , 2016).
Cloud architecture provides the facility of private cloud and private clouds are specifically developed for enterprise applications. These clouds are meant to be used by organizations separately and the platform does not use physical resources on a shared basis. The resources can be distributed internally or externally on demand (Wei et al . , 2014). One of the major advantages of private cloud is that the database is secured using multiple level of security layer. It protects the data from malicious attack by restricting shared resources to access protected and private organizational information (Fehling et al., 2014). Cloud providers have gone one step further to achieve more security by ensuring that the hardware that is used for the services is completely dedicated to the organizational use and any attempt to temper with the resources is completely restricted (Pulier , Martinez & Hill , 2015). The virtual private network that is used for the cloud services is fully encrypted with advance encryption technology that takes the security of the system to top level as specified in the article.
Big data is so large in terms of volume, velocity and variety that it can be stored using traditional computer storage systems. To store the large amount of data that is generated everyday it needs special storage services. To store and process such huge amount of data that comes in million and billion of terabytes , it requires scalability, ability to tolerate fault and availability of the storage system. Cloud computing provides all these facility by the use of hardware visualization (Yu et al . , 2017). Cloud computing makes big data available, scalable and at the same time fault tolerant (Elazhary, 2014).
One of the biggest challenges that organizations encounter is that they need to create backup of data and schedule the backup process in such a way that their day to day activities does not get affected. To create backup a large amount of storage is needed. With cloud storage the process become automatic and they need to care less about the capacity of the storage as the cloud comes with literally an unlimited amount of storage (Mehr et al., 2015). The storage is definitely not similar to traditional physical storage; it is a virtual storage service that is managed by large physical data servers located remotely (Chawla, Molloy & Hormuth, 2016).
With the constant rise in demand for advanced computation, that involves large amount of storage and complex infrastructure, enterprises are facing issues increased energy and power consumption that in turn increase the cost of the production ( Mastelic et al., 2015).
To reduce energy consumption, cloud providers use hardwares that are energy efficient which reduce the power consumption at data center as well as virtual machine level (Kaur & Chana , 2015).
When cloud platform is used for data storage activities such as Amazon Simple Storage which can be used to store document, video files, it is relatively more power efficient than traditional storage systems that demands a lot of power to operate (Li et al., 2016).
Energy optimization is achieved by effective combination of virtual network topologies. Thermal status of computer hardwares are checked on a regular basis to ensure optimum services to the end users (Fiandrino et al., 2017 ).
With cloud services, organizations are storing sensitive and valuable data remotely and third party service providers manage those data (Avram, 2014). The author suggests that before adopting the cloud technology, organizations should consider that the data that is stored in cloud is not always secured and the security depends on the quality of service provider . It is always important to chose a reliable service provider like Amazon , Microsoft , IBM with Amazon being the current market leader in terms of customer base and service quality. It should be noted that cloud computing is powered by internet and as internet is not completely secure there is always a possibility of data theft as specified by the article.
Cloud storage offers a lot of benefits for data storage in terms of accessibility, scalability and speed of operation. Still there are few drawbacks that organizations should consider before investing in the budding technology that has created a lot of buzz in the industry within a very short time since the adoption (Yang & Lin , 2015).
According to the article, cloud storage comes in various forms in terms of service quality and storage capacity. It also mentions that the capacity of the storage depends on the bandwidth allowance, which is again determined by the pricing of the service. The more premium the service is, higher the bandwidth available for the storage. The pricing of the service varies depending on the service provider one chose for the business. Once the allowed bandwidth is suppressed, users have to pay a handsome amount for further use as per the information provided by the authors.
Cloud computing provide ways to make computing infrastructure power efficient yet the technology needs improvement. Cloud applications are conveyed in remote data centers (DCs) where servers with high capacity and storage systems are found (Almorsy , Grundy & Muiler , 2016). A speedy advancement of enthusiasm for cloud based organizations comes to fruition into establishment of enormous server ranches eating up high measure of electrical power. Powerful model is required for complete establishment to decrease helpful costs while keeping up vital Quality of Service (QoS) as suggested by the article.
Conclusion:
Even though cloud computing has some drawbacks in terms of security, capacity and cost effectiveness, based on the report it can be concluded that the benefits that cloud computing offers is undoubtedly makes it one of the highly demanding technology in the digital market. It has revolutionized the way traditional computing systems used to operate. The technology , being relatively new has a lot areas where significant improvement is needed but the capability of cloud computing for big data management is unmatched. Based on the current scenario it will not be unfair to say that the demand for the service will continue to grow in the coming years to use big data in more effective way.
References:
Almorsy, M., Grundy, J., & Müller, I. (2016). An analysis of the cloud computing energy effeciency problem. arXiv preprint arXiv:1609.01107.
Avram, M. G. (2014). Advantages and challenges of adopting cloud computing from an enterprise perspective. Procedia Technology, 12, 529-534.
Daas, P. J., Puts, M. J., Buelens, B., & van den Hurk, P. A. (2015). Big data as a source for official statistics. Journal of Official Statistics, 31(2), 249.
De Mauro, A., Greco, M., & Grimaldi, M. (2015, February). What is big data? A consensual definition and a review of key research topics. In AIP conference proceedings (Vol. 1644, No. 1, pp. 97-104). AIP.
Elazhary, H. (2014). Cloud computing for big data. MAGNT Res Rep, 2(4), 135-144.
Fehling, C., Leymann, F., Retter, R., Schupeck, W., & Arbitter, P. (2014). Cloud computing patterns: fundamentals to design, build, and manage cloud applications. Springer Science & Business Media.
Fiandrino, C., Kliazovich, D., Bouvry, P., & Zomaya, A. Y. (2017). Performance and energy efficiency metrics for communication systems of cloud computing data centers. IEEE Transactions on Cloud Computing, 5(4), 738-750.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98-115.
Kaur, T., & Chana, I. (2015). Energy efficiency techniques in cloud computing: A survey and taxonomy. ACM Computing Surveys (CSUR), 48(2), 22.
Li, Z., Dai, Y., Chen, G., & Liu, Y. (2016). Toward network-level efficiency for cloud storage services. In Content Distribution for Mobile Internet: A Cloud-based Approach(pp. 167-196). Springer Singapore.
Mastelic, T., Oleksiak, A., Claussen, H., Brandic, I., Pierson, J. M., & Vasilakos, A. V. (2015). Cloud computing: Survey on energy efficiency. Acm computing surveys (csur), 47(2), 33.
Mehr, J. D., Murphy, E. E., Virk, N., & Sosnosky, L. M. (2015). U.S. Patent No. 8,935,366. Washington, DC: U.S. Patent and Trademark Office.
Pulier, E., Martinez, F., & Hill, D. C. (2015). U.S. Patent No. 8,931,038. Washington, DC: U.S. Patent and Trademark Office.
Rittinghouse, J. W., & Ransome, J. F. (2016). Cloud computing: implementation, management, and security. CRC press.
Wei, L., Zhu, H., Cao, Z., Dong, X., Jia, W., Chen, Y., & Vasilakos, A. V. (2014). Security and privacy for storage and computation in cloud computing. Information Sciences, 258, 371-386.
Yang, H. L., & Lin, S. L. (2015). User continuance intention to use cloud storage service. Computers in Human Behavior, 52, 219-232.
Yu, Y., Au, M. H., Ateniese, G., Huang, X., Susilo, W., Dai, Y., & Min, G. (2017). Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage. IEEE Transactions on Information Forensics and Security, 12(4), 767-778
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