An end-to-end model-based approach to support big data analytics development

Hourieh Khalajzadeh, Andrew J. Simmons, Mohamed Almorsy Abdelrazek, John Grundy, John Hosking, Qiang He

Research output: Contribution to journalArticleResearchpeer-review

Abstract

We present BiDaML 2.0, an integrated suite of visual languages and supporting tool to help multidisciplinary teams with the design of big data analytics solutions. BiDaML tool support provides a platform for efficiently producing BiDaML diagrams and facilitating their design, creation, report and code generation. We evaluated BiDaML using two types of evaluations, a theoretical analysis using the “physics of notations”, and an empirical study with 1) a group of 12 target end-users and 2) five individual end-users. Participants mostly agreed that BiDaML was straightforward to understand/learn, and prefer BiDaML for supporting complex data analytics solution modeling than other modeling languages.

Original languageEnglish
Article number100964
Number of pages20
JournalJournal of Computer Languages
Volume58
DOIs
Publication statusPublished - Jun 2020

Keywords

  • Big data analytics
  • Big data modeling
  • Big data toolkits
  • Domain-specific visual languages
  • End-user tools
  • Multidisciplinary teams

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