Big data technologies are rapidly gaining popularity and become widely used, thus, making the choice of developing methodologies including the approaches for requirements analysis more acute. There is a position that in the context of the Data Warehousing (DW), similar to other Decision Support Systems (DSS) technologies, defining information requirements (IR) can increase the chances of the project to be successful with its goals achieved. This way, it is important to examine this subject in the context of Big data due to the lack of research in the field of Big data requirements analysis. This paper gives an overview of the existing methods associated with Big data technologies and requirements analysis, and provides an evaluation by three types of criteria: (i) general characteristics, (ii) requirements analysis related, and (iii) Big data technologies related criteria. We summarize on the requirements analysis process in Big data projects, and explore solutions on how to (semi-) automate requirements engineering phases.
CITATION STYLE
Kozmina, N., Niedrite, L., & Zemnickis, J. (2018). Information requirements for big data projects: A review of state-of-the-art approaches. In Communications in Computer and Information Science (Vol. 838, pp. 73–89). Springer Verlag. https://doi.org/10.1007/978-3-319-97571-9_8
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