IDEAS home Printed from https://ideas.repec.org/a/sgh/annals/i38y2015p167-178.html
   My bibliography  Save this article

Big Data quality analysis on data retrieved from websites

Author

Listed:
  • Jacek Maślankowski

    (Uniwersytet Gdański)

Abstract

The article presents a proposition of a Big Data quality framework in terms of processing Big Data sources to produce statistical information. The case used in the article concerns job offers that generate information about the demand of the labour market. The analyses has resulted in a suggestion of several quality dimensions with indicators.

Suggested Citation

  • Jacek Maślankowski, 2015. "Big Data quality analysis on data retrieved from websites," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 38, pages 167-178.
    • Handle: RePEc:sgh:annals:i:38:y:2015:p:167-178
    as

    Download full text from publisher

    File URL: http://rocznikikae.sgh.waw.pl/p/roczniki_kae_z38_11.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Erik W. Kuiler, 2014. "From Big Data to Knowledge: An Ontological Approach to Big Data Analytics," Review of Policy Research, Policy Studies Organization, vol. 31(4), pages 311-318, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Thao, Vu Thi & Wegelin, Philipp & von Arx, Widar, 2017. "Are statutory passenger watchdogs effective in representing passenger interests in public transport?," Transport Policy, Elsevier, vol. 58(C), pages 1-9.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gastaldi, Luca & Pietrosi, Astrid & Lessanibahri, Sina & Paparella, Marco & Scaccianoce, Antonio & Provenzale, Giuseppe & Corso, Mariano & Gridelli, Bruno, 2018. "Measuring the maturity of business intelligence in healthcare: Supporting the development of a roadmap toward precision medicine within ISMETT hospital," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 84-103.

    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:sgh:annals:i:38:y:2015:p:167-178. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Michał Bernardelli (email available below). General contact details of provider: https://edirc.repec.org/data/sgwawpl.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.