IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05143333.html
   My bibliography  Save this paper

Utilizing Big Data Analytics and Business Intelligence for Improved Decision-Making at Leading Fortune Company

Author

Listed:
  • Oluwaseun Oladeji Olaniyi

    (University of the Cumberlands, 104 Maple Drive, Williamsburg, KY 40769, United States of America.)

  • Anthony Idoko Abalaka

    (Ashland University, 401 College Avenue, Ashland OH, 44805, United States of America.)

  • Samuel Oladiipo Olabanji

    (Midcontinent Independent System Operator (Miso energy) 720 City Center Drive, Carmel, Indiana 46032, United States of America.)

Abstract

The present study evaluates Walmart's existing big data analytics with business intelligence techniques, accentuating their strengths and weaknesses, and suggests improvements for implementation and maintenance through the literature review of the scholarly journals addressing similar topics. Big data analytics is receiving loads of attention globally in the business environment within every sector of the economy. Incorporating the job plan as an additional input component in their models would be beneficial for Walmart to improve the precision and appropriateness of their data analysis and decision-making procedures. Walmart is a company that heavily invests in utilizing big data to improve its operations; this includes optimizing in-store experiences and predicting product trends. Scholarly articles emphasize the importance of advanced data analytics tools like MapReduce and Apache Spark for effective big data strategies. Social media content influences engagement and sentiment. Social network data aids sales forecasting but presents challenges. Big data analytics with business intelligence enhances performance and decision-making. Walmart's success in big data analytics relies on a data-driven culture but faces security challenges. Many Fortune 1000 companies adopt innovative solutions to improve performance and customer experiences but require significant resources. Embracing big data analytics with business intelligence remains a compelling investment for sustaining a competitive edge. Walmart's success in big data analytics is due to a data-driven culture and advanced infrastructure, including the Data Café.

Suggested Citation

  • Oluwaseun Oladeji Olaniyi & Anthony Idoko Abalaka & Samuel Oladiipo Olabanji, 2023. "Utilizing Big Data Analytics and Business Intelligence for Improved Decision-Making at Leading Fortune Company," Post-Print hal-05143333, HAL.
    • Handle: RePEc:hal:journl:hal-05143333
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    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:hal:journl:hal-05143333. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.