International Journal of Research in Signal Processing, Computing & Communication System Design

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A Study on Human Centric Agile Methodologies with Big Data & Predictive Analytics in Software Development


Affiliations
1 Dept. of CSE, UOT, Jaipur, Rajasthan, India
2 NIC, Hyderabad, Telangana, India
3 Dept. of CSE, BVRIT, Narsapur, Telangana, India
     

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This paper proposes an agile model-based systems engineering (SE) methodology to engineer the contemporary large, complex, and interdisciplinary systems of systems. This paper introduces the reader the background of Big Data Analytics and how efficiently Agile methodology can be applied to achieve the business goal. The journal focus on giving background of Big Data and how using Agile practices such as iterative, incremental, and evolutionary style of development can be applied for Big Data Analytics. This methodology brings in the advantage of involving business community during development and continuous delivery of working user features. The Agile uses a universal and intuitive SE base process, reducing the complexity and intricacy of the base methods, emphasizing the agile principles such as continuous communication, feedback and stakeholders’ involvement, short iterations, and rapid response, and rousing the utilization of a coherent system model developed through the benchmark systems graphical modeling languages. The Agile methodology also includes a supporting graphical tool that aims to be an agile instrument to be used by systems engineers in a model-based development environment.

Keywords

Agile, Big Data Analytics, Big Data, Data Analyst, Model-based System Engineering (MBSE), Software Engineering.
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  • D. H. Rhodes, “Addressing systems engineering challenges through collaborative research,” in SEARI-Systems Engineering Advancement Research Initiative, Cambridge, MA: MIT Press, 2008.

  • S. Sheard, and A. Mostashari, “Principles of complex systems for systems engineering,” Systems Engineering, vol. 12, no. 4, pp. 295-311, September 2009.

  • A. L. F. A. Ramos, J. V. Ferreira, and J. Barceló, “Revisiting the similar process to engineer the contemporary systems,” Journal of Systems Science and Systems Engineering, vol. 19, no. 3, pp. 321-350, September 2010.

  • S. Friedenthal, A. Moore, and R. Steiner, A Practical Guide to SysML: The Systems Modeling Language, Burlington, MA: OMG Press, 2008.

  • J. O. Grady, “Universal architecture description framework,” Systems Engineering, vol. 12, no. 2, pp. 91-116, May 2009.

  • R. Jurney, Agile Data Science, 2013.

  • M. Poppendieck, and T. Poppendieck, Lean Software Development: An Agile Toolkit, Addison-Wesley, Boston, 2003.

  • V. Mayer-Schonberger, and K. N. Cukier, Big Data: A Revolution That Will Transform How We Live, Work, and Think, 2013.

  • M. Poppendieck, and T. Poppendieck, Leading Lean Software Development: Results Are not the Point, Addison-Wesley, Upper Saddle River, NJ, 2010.


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  • A Study on Human Centric Agile Methodologies with Big Data & Predictive Analytics in Software Development

Abstract Views: 418  |  PDF Views: 0

Authors

T. Sasi Vardhan
Dept. of CSE, UOT, Jaipur, Rajasthan, India
C. S. R. Prabhu
NIC, Hyderabad, Telangana, India
V. Anitha
Dept. of CSE, BVRIT, Narsapur, Telangana, India

Abstract


This paper proposes an agile model-based systems engineering (SE) methodology to engineer the contemporary large, complex, and interdisciplinary systems of systems. This paper introduces the reader the background of Big Data Analytics and how efficiently Agile methodology can be applied to achieve the business goal. The journal focus on giving background of Big Data and how using Agile practices such as iterative, incremental, and evolutionary style of development can be applied for Big Data Analytics. This methodology brings in the advantage of involving business community during development and continuous delivery of working user features. The Agile uses a universal and intuitive SE base process, reducing the complexity and intricacy of the base methods, emphasizing the agile principles such as continuous communication, feedback and stakeholders’ involvement, short iterations, and rapid response, and rousing the utilization of a coherent system model developed through the benchmark systems graphical modeling languages. The Agile methodology also includes a supporting graphical tool that aims to be an agile instrument to be used by systems engineers in a model-based development environment.

Keywords


Agile, Big Data Analytics, Big Data, Data Analyst, Model-based System Engineering (MBSE), Software Engineering.

References