Deakin University
Browse

A Practical, Collaborative Approach for Modeling Big Data Analytics Application Requirements

Version 2 2024-06-04, 13:05
Version 1 2020-11-04, 07:02
conference contribution
posted on 2024-06-04, 13:05 authored by Hourieh KhalajzadehHourieh Khalajzadeh, A Simmons, Mohamed AbdelrazekMohamed Abdelrazek, J Grundy, J Hosking, Q He, P Ratnakanthan, A Zia, M Law
© 2020 Copyright held by the owner/author(s). Data analytics application development introduces manychallenges including: new roles not in traditional softwareengineering practices e.g. data scientists and data engineers; useof sophisticated machine learning (ML) model-based approaches;uncertainty inherent in the models; interfacing with models tofulfill software functionalities; deploying models at scale andrapid evolution of business goals and data sources. We describeour Big Data Analytics Modeling Languages (BiDaML) toolset tobring all stakeholders around one tool to specify, model anddocument big data applications. We report on our experienceapplying BiDaML to three real-world large-scale applications.Our approach successfully supports complex data analyticsapplication development in industrial settings.

History

Pagination

256-257

Location

ELECTR NETWORK

Start date

2020-06-27

End date

2020-07-19

ISSN

0270-5257

ISBN-13

9781450371223

Language

English

Publication classification

E3 Extract of paper

Title of proceedings

Proceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering: Companion, ICSE-Companion 2020

Event

42nd ACM/IEEE International Conference on Software Engineering - Companion Proceedings (ICSE-Companion)

Publisher

IEEE

Series

International Conference on Software Engineering

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC