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

被引：11
|
作者：
Khalajzadeh, Hourieh [1 ]
Simmons, Andrew J. [2 ]
Abdelrazek, Mohamed [3 ]
Grundy, John [1 ]
Hosking, John [4 ]
He, Qiang [5 ]
机构：
[1] Monash Univ, Clayton, Vic, Australia
[2] Deakin Univ, Appl Artificial Intelligence Inst A2I2, Geelong, Vic, Australia
[3] Deakin Univ, Sch Informat Technol, Geelong, Vic, Australia
[4] Univ Auckland, Fac Sci, Auckland, New Zealand
[5] Swinburne Univ Technol, Sch Software & Elect Engn, Melbourne, Vic, Australia
来源：
JOURNAL OF COMPUTER LANGUAGES | 2020年 / 58卷
关键词：
Big data analytics; Big data modeling; Big data toolkits; Domain-specific visual languages; Multidisciplinary teams; End-user tools; VISUAL NOTATIONS; ENVIRONMENT; LANGUAGE; SUITE;
D O I：
10.1016/j.cola.2020.100964
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
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.
引用
收藏
页数：20
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