Big data on cloud for government agencies: benefits, challenges, and solutions

Big Data and Cloud computing are the most important technologies that give the opportunity for government agencies to gain a competitive advantage and improve their organizations. On one hand, Big Data implementation requires investing a significant amount of money in hardware, software, and workforce. On the other hand, Cloud Computing offers an unlimited, scalable and on-demand pool of resources which provide the ability to adopt Big Data technology without wasting on the financial resources of the organization and make the implementation of Big Data faster and easier. The aim of this study is to conduct a systematic literature review in order to collect data to identify the benefits and challenges of Big Data on Cloud for government agencies and to make a clear understanding of how combining Big Data and Cloud Computing help to overcome some of these challenges. The last objective of this study is to identify the solutions for related challenges of Big Data. Four research questions were designed to determine the information that is related to the objectives of this study. Data is collected using literature review method and the results are deduced from there.

[1]  Steven B. Leeb,et al.  NilmDB: The Non-Intrusive Load Monitor Database , 2014, IEEE Transactions on Smart Grid.

[2]  Yong Zhao,et al.  Optimized Cloud Resource Management and Scheduling: Theories and Practices , 2014 .

[3]  Gloria E. Phillips-Wren,et al.  An analytical journey towards big data , 2015, J. Decis. Syst..

[4]  Shashank Pushkar,et al.  Cloud computing challenges and implementations , 2016, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT).

[5]  Sravanthi Kanchi,et al.  Challenges and Solutions in Big Data Management -- An Overview , 2015, 2015 3rd International Conference on Future Internet of Things and Cloud.

[6]  K Ham,et al.  OpenRefine (version 2.5). . Free, open-source tool for cleaning and transforming data. , 2013 .

[7]  Mohammad Masdari,et al.  Using Cloud Computing for E-Government: Challenges and Benefits , 2013 .

[8]  Ziya Karakaya.  Software engineering issues in big data application development , 2017, 2017 International Conference on Computer Science and Engineering (UBMK).

[9]  Silvana Trimi,et al.  Big-data applications in the government sector , 2014, Commun. ACM.

[10]  Pearl Brereton,et al.  Performing systematic literature reviews in software engineering , 2006, ICSE.

[11]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[12]  Syed Mohd Ali,et al.  Big data visualization: Tools and challenges , 2016, 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I).

[13]  In Lee,et al.  Big data: Dimensions, evolution, impacts, and challenges , 2017 .

[14]  Yingxu Wang,et al.  Big Data Analytics on the Characteristic Equilibrium of Collective Opinions in Social Networks , 2014, Int. J. Cogn. Informatics Nat. Intell..

[15]  Elisa Bertino,et al.  Big Data -- Opportunities and Challenges Panel Position Paper , 2013, 2013 IEEE 37th Annual Computer Software and Applications Conference.

[16]  Sri Lanka,et al.  A Review on Cloud Computing Adoption: An Exploratory Analysis , 2015 .

[17]  Gang Li,et al.  Big data related technologies, challenges and future prospects , 2015, J. Inf. Technol. Tour..

[18]  Sanjay Kumar Dubey,et al.  Analysis of requirements for Big Data Adoption to maximize IT Business Value , 2015, 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions).

[19]  Amit P. Sheth,et al.  From Data to Actionable Knowledge: Big Data Challenges in the Web of Things , 2013, IEEE Intell. Syst..

[20]  Rahul Johari,et al.  Big Data: A Boon or Bane - The Big Question , 2016, 2016 Second International Conference on Computational Intelligence & Communication Technology (CICT).

[21]  Jorina Smeda,et al.  Benefits, business considerations and risks of big data , 2015 .

[22]  Rakesh Sharma,et al.  BIG DATA: OPPORTUNITIES AND CHALLENGES , 2015 .

[23]  Z. Irani,et al.  Critical analysis of Big Data challenges and analytical methods , 2017 .

[24]  Shrisha Rao,et al.  A Mechanism Design Approach to Resource Procurement in Cloud Computing , 2014, IEEE Transactions on Computers.

[25]  Sanchita Garg,et al.  Big Data: Analysis , Challenges and Solutions , 2015 .

[26]  Guillem Pratx,et al.  Cloud computing for big data , 2019, Big Data in Radiation Oncology.

[27]  Mandeep Pannu,et al.  The impact of big data on government processes , 2016, 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON).

[28]  Wenhong Tian,et al.  Big Data Technologies and Cloud Computing , 2015 .

[29]  John Chang,et al.  The Haves and the Have-Nots , 1989 .

[30]  Manolis Tzagarakis,et al.  On a meaningful exploitation of machine and human reasoning to tackle data-intensive decision making , 2013, Intell. Decis. Technol..

[31]  Shalini Kumari,et al.  A Review paper on Big Data , 2019, International Journal of Mobile Computing and Application.

[32]  Ali Yazici,et al.  Systematic Mapping Study on Performance Scalability in Big Data on Cloud Using VM and Container , 2016, AIAI.

[33]  Axel-Cyrille Ngonga Ngomo,et al.  Big Data Acquisition , 2016, New Horizons for a Data-Driven Economy.

[34]  Mara Carina Roldn.  Pentaho 3.2 Data Integration: Beginner's Guide , 2010 .

[35]  Narasimha Rao Vajjhala,et al.  Big Data using Cloud Computing - Opportunities for Small and Medium-sized Enterprises , 2016 .

[36]  M. Deshpande,et al.  International Research Journal of Engineering and Technology (IRJET) , 2016 .

[37]  Li Xu,et al.  Toward better data veracity in mobile cloud computing: A context-aware and incentive-based reputation mechanism , 2017, Inf. Sci..

[38]  Dmitry Namiot,et al.  On Big Data Stream Processing , 2015 .