IDEAS home Printed from https://ideas.repec.org/a/aes/infoec/v16y2012i2p116-127.html
   My bibliography  Save this article

Distributed Parallel Architecture for "Big Data"

Author

Listed:
  • Catalin BOJA
  • Adrian POCOVNICU
  • Lorena BATAGAN

Abstract

This paper is an extension to the "Distributed Parallel Architecture for Storing and Processing Large Datasets" paper presented at the WSEAS SEPADS’12 conference in Cambridge. In its original version the paper went over the benefits of using a distributed parallel architecture to store and process large datasets. This paper analyzes the problem of storing, processing and retrieving meaningful insight from petabytes of data. It provides a survey on current distributed and parallel data processing technologies and, based on them, will propose an architecture that can be used to solve the analyzed problem. In this version there is more emphasis put on distributed files systems and the ETL processes involved in a distributed environment.

Suggested Citation

  • Catalin BOJA & Adrian POCOVNICU & Lorena BATAGAN, 2012. "Distributed Parallel Architecture for "Big Data"," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 16(2), pages 116-127.
  • Handle: RePEc:aes:infoec:v:16:y:2012:i:2:p:116-127
    as

    Download full text from publisher

    File URL: http://www.revistaie.ase.ro/content/62/12%20-%20Boja.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shahriar Akter & Samuel Fosso Wamba, 2016. "Big data analytics in E-commerce: a systematic review and agenda for future research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 173-194, May.
    2. Acharya, Abhilash & Singh, Sanjay Kumar & Pereira, Vijay & Singh, Poonam, 2018. "Big data, knowledge co-creation and decision making in fashion industry," International Journal of Information Management, Elsevier, vol. 42(C), pages 90-101.
    3. Abhishek Behl & Pankaj Dutta & Stefan Lessmann & Yogesh K. Dwivedi & Samarjit Kar, 2019. "A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach," Information Systems and e-Business Management, Springer, vol. 17(2), pages 285-318, December.
    4. Yasser AL-HADAD & Razvan Daniel ZOTA, 2016. "Implementing Business Intelligence System - Case Study," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 7(1), pages 35-44, August.
    5. Daniel HOMOCIANU & Dinu AIRINEI, 2015. "Some Behavioral Considerations on the GPS4GEF Cloud-Based Generator of Evaluation Forms with Automatic Feedback and References to Interactive Support Content," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 19(3), pages 19-31.
    6. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aes:infoec:v:16:y:2012:i:2:p:116-127. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Paul Pocatilu (email available below). General contact details of provider: https://edirc.repec.org/data/aseeero.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.