Data Engineering and AI for BI Efficiency: Roles, Permissions, and Cloud Storage

Data Engineering and AI for BI Efficiency: Roles, Permissions, and Cloud Storage

Authors

  • Robin Verma

Abstract

This research paper explores data engineering approaches aimed at enhancing team collaboration and analyst productivity within business intelligence (BI) and cloud environments. Focusing on efficient role assignments, permission management, visual analysis techniques, and optimized data storage strategies, the study delves into the intricacies of modern BI systems. By leveraging advanced data engineering methodologies, organizations can streamline processes, empower analysts, and maximize the value derived from BI initiatives. Additionally, the paper highlights the role of artificial intelligence (AI) in improving BI efficiency through advanced analytics, predictive modeling, and automated decision-making. Through a synthesis of best practices and innovative techniques, this paper provides valuable insights into optimizing BI workflows for enhanced decision-making and operational efficiency in today's dynamic business landscape.

References

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Published

2024-06-15

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Articles

How to Cite

Data Engineering and AI for BI Efficiency: Roles, Permissions, and Cloud Storage. (2024). International Numeric Journal of Machine Learning and Robots, 8(8), 1-18. https://injmr.com/index.php/fewfewf/article/view/78

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