Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia

Research Article

A Study Review of Common Big Data Architecture for Small-medium Enterprise

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  • @INPROCEEDINGS{10.4108/eai.12-10-2019.2296535,
        author={Ridwan Fadjar Septian and Fajri  Abdillah and Tajhul Faijin Aliyudin},
        title={A Study Review of Common Big Data Architecture for Small-medium Enterprise},
        proceedings={Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia},
        publisher={EAI},
        proceedings_a={MSCEIS},
        year={2020},
        month={7},
        keywords={big data architecture small-medium enterprise open-source large-scale dataset data engineering},
        doi={10.4108/eai.12-10-2019.2296535}
    }
    
  • Ridwan Fadjar Septian
    Fajri Abdillah
    Tajhul Faijin Aliyudin
    Year: 2020
    A Study Review of Common Big Data Architecture for Small-medium Enterprise
    MSCEIS
    EAI
    DOI: 10.4108/eai.12-10-2019.2296535
Ridwan Fadjar Septian1,*, Fajri Abdillah2, Tajhul Faijin Aliyudin3
  • 1: Master of Information System, Faculty of Postgraduate, Universitas Komputer Indonesia, Indonesia
  • 2: Senior Software Engineer, Horangi Cyber Security
  • 3: Senior Software Engineer, Tado.live
*Contact email: ridwanbejo@gmail.com

Abstract

This paper will be composed by conducting a document review and collect papers that related to big data solution and infrastructure. The survey is trying to cover the phases for building a common big data pipelines by following these structures: enterprise vision and mission that affect the big data architecture, defining the data sources, building the backend services to collect the datapoint from the data sources, utilize the data pipeline to prevent data loss, consuming the data pipeline message and deliver it to the data storage, build the raw data storage, define business-driven data visualization and analytics, build the ETL, build business-oriented data storage, applying statistical and machine learning, perform the business-driven visualization and implementing the monitoring for the big data pipelines. The survey will emphasize that many big data components could help the small-medium enterprise to tackle their big data operational issues.