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From Data to Decisions: Harnessing the Potential of Big Data Analytics and Machine Learning

EasyChair Preprint no. 11861

8 pagesDate: January 24, 2024


In the era of information abundance, this paper embarks on an exploration of the transformative synergy between big data analytics and machine learning, dissecting their evolution and impact on decision-making processes. Through a meticulous review, the paper unveils the methodologies employed, highlights real-world results, scrutinizes challenges, proposes treatments, and navigates the ethical considerations surrounding these technologies. The journey from data to decisions is not merely a technological shift; it is a strategic imperative for organizations seeking to thrive in an era defined by data-driven insights. As we navigate this landscape, the paper offers insights into the implications for the future, acknowledges collaborative efforts, and reflects on the profound changes these technologies herald. It is an invitation for organizations to not only embrace this evolution but to actively shape their destinies in the data-driven narrative. This paper explores the transformative power of big data analytics and machine learning in converting vast datasets into actionable insights. Through a comprehensive review, it delves into the methodologies employed, results achieved, challenges faced, and potential treatments, ultimately highlighting the profound impact on decision-making processes.

Keyphrases: Analytics, Big Data, Challenges, Data-driven insights, decision making, machine learning, methodology, Treatments

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {William Jack and Mocha Mush},
  title = {From Data to Decisions: Harnessing the Potential of Big Data Analytics and Machine Learning},
  howpublished = {EasyChair Preprint no. 11861},

  year = {EasyChair, 2024}}
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