500-Word Summary of Article About Big Data in Cloud Computing

TO:           Prof.  Ellis

FROM:     Norbert Derylo

DATE:     Oct 6, 2021

SUBJECT:     500-Word Summary of Article About Big Data in Cloud Computing

A major challenge of working with big data is using cloud computing. Cloud computing provides many benefits that can help with big data. The study focuses on the various interactions between cloud computing and big data. 

Big data is data that is difficult to store due to its volume and variety. In the article big data is defined as “a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling the high velocity capture, discovery, and/or analysis.” Big data can be described with four metrics: volume, variety, velocity, value. Big data can also be classified by five aspects: data sources, content format, data stores, data staging, data processing.  Each classification of data has its own characteristics and complexities. 

Cloud computing is the next generation of computing in professional settings. Cloud computing has many advantages over current computing methods. The increased popularity of wireless devices has allowed cloud computing to become extremely useful. Cloud computing and big data work hand-in-hand, cloud computing being the base on which big data thrives and expands. Due to the variety of big data, different forms of cloud computing will not work for all forms of big data. 

The two sets of data on the relationship between big data and cloud computing come from scholarly sources and the different vendors of cloud computing. Case studies from different vendors demonstrate the extensive variety of research that uses cloud computing. Swift Key used cloud computing to scale its services for demand. 343 Industries used cloud computing to make their game more enjoyable. redBus used cloud computing to improve customer service for online bus ticketing. Nokia used cloud computing to process petabytes of data from their phone network. Alacer used cloud computing to improve response times to system outages. Scholar studies also used cloud computing for big data projects. Scholars studying DNA have used cloud computing to dramatically increase the speed at which they analyze DNA sequences. A case study showed that cloud computing can acquire and analyze extremely large data sources, for example data from social media. A study of microscopic images used cloud computing to submit data processing jobs to the cloud. A study used cloud computing to show that you can use cloud computing as a backup to massive failures of other computing services. 

Data integrity is a data security concern and can be a concern in cloud computing as well. Transforming big data for analysis is a challenge and one of the reasons big data is not as popular as it should be. Data quality can be quite variable and cause concerns with big data. Big data allows for various different sources of data which might not follow the same structure. Privacy is also one of the biggest concerns of cloud storage. Encryption is the most popular way to keep cloud data safe. Data that is encrypted is not scalable and the computation time used for it is not practical for big data. Another possible solution is using algorithms to determine how to give out data to prevent leaks. Although studies have addressed multiple issues with cloud computing, there are few tools that can patch up the problems. Data staging is an issue involving the various different formats big data collects. There have been solutions to improve distributed storage systems, however they dont fix all the problems with optimization and accessibility. The current algorithms from data analysis are too unoptimized for the scalability of big data. Data security still and always will be an ongoing problem in cloud computing and big data. 
[1]Hashem, I.  A.  T. , Yaqoob, I. , Anuar, N.  B. , Mokhtar, S. , Gani, A. , & Ullah Khan, S.  “The rise of “big data” on cloud computing: Review and open research issues.  Information Systems” Information Systems.  2015 Vol.  47, p98–115.  https://doi. org/10. 1016/j. is. 2014. 07. 006

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