Utilizing Big Data Analytics and Business Intelligence for Improved Decision-Making at Leading Fortune Company
Oluwaseun Oladeji Olaniyi, Anthony Idoko Abalaka, Samuel Oladiipo Olabanji
Journal of Scientific Research and Reports · pp. 64–72 · Published 14 Sep 2023
10.9734/jsrr/2023/v29i91785Abstract
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.
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Showing 20 of 26 known citations — external sources report more than can currently be individually listed.
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