Synergistic review of automation impact of big data, AI, and ML in current data transformative era [version 2; peer review: 2 approved, 1 approved with reservations]
The convergence of automation, big data analytics (BDA), artificial intelligence (AI), and machine learning (ML) has ushered in a new era of technological advancement, reshaping industries, and societies worldwide. This review research work delves into the transformative impact of these technologies...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
F1000 Research Ltd
2025-05-01
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| Series: | F1000Research |
| Subjects: | |
| Online Access: | https://f1000research.com/articles/14-253/v2 |
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| Summary: | The convergence of automation, big data analytics (BDA), artificial intelligence (AI), and machine learning (ML) has ushered in a new era of technological advancement, reshaping industries, and societies worldwide. This review research work delves into the transformative impact of these technologies, focusing on their applications across various sectors. The study covers six key sectors: healthcare, banking, finance, retail, real estate, and agriculture, highlighting how these industries leverage automated systems and data analytics to enhance operations, manage risks, and improve decision-making processes. Drawing results from over 1,000 research papers and categorizing them into 100 key studies specifics, this survey-based review underscores the critical role of big data in enabling predictive analytics, improving outcomes, and driving innovation across sectors. The review research work explores how industries utilize vast data volumes from diverse sources to derive actionable insights, forecast trends, and optimize processes. Key applications included in the review are from the domains of disease prediction and electronic health record management in healthcare , fraud detection and credit risk assessment in banking and finance, consumer behavior analysis and inventory optimization in retail, market trend forecasting in real estate, and disaster risk management in agriculture. The paper also discusses the challenges including data quality, scalability, and privacy paving way towards future directions of big data analytics, emphasizing the need for machine-independent solutions, data security, and ethical considerations in the evolving landscape of data-driven decision-making. |
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| ISSN: | 2046-1402 |