The Quantum Frontier: How Quantum Computing Will Transform Data Science

Quantum computing represents a paradigm shift in computational capability that promises to transform data science by addressing problems currently intractable on classical systems. As global data creation expands exponentially, quantum technologies emerge as potential solutions for managing unprecedented complexity. This article examines the fundamental advantages of quantum computing, including exponential parallelism through superposition, management of computational complexity, and the ability to solve previously unsolvable problems. High-impact application domains are explored, including machine learning transformation, optimization at unprecedented scales, cryptography and data security, molecular simulation for drug discovery, and complex systems modeling for climate prediction. While these opportunities appear transformative, substantial technical challenges remain, including quantum decoherence, hardware scalability constraints, and algorithmic development gaps. The path forward likely involves hybrid quantum-classical architectures, targeted applications in big data analytics, enhanced AI systems, and revolutionary simulation capabilities for complex systems.

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Publication Details

Journal
International Journal of English Literature and Social Sciences
Published
2025-01-01
DOI
https://doi.org/10.22161/ijels.104.52
Citations
1
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
2.48
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article

The Quantum Frontier: How Quantum Computing Will Transform Data Science

Vinu E. Venugopal
1 citations
International Journal of English Literature and Social Sciences
Quantum Computing Algorithms and Architecture
2.48
article

The Quantum Frontier: How Quantum Computing Will Transform Data Science

Vinu E. Venugopal
article en
1 citations

Abstract

Quantum computing represents a paradigm shift in computational capability that promises to transform data science by addressing problems currently intractable on classical systems. As global data creation expands exponentially, quantum technologies emerge as potential solutions for managing unprecedented complexity. This article examines the fundamental advantages of quantum computing, including exponential parallelism through superposition, management of computational complexity, and the ability to solve previously unsolvable problems. High-impact application domains are explored, including machine learning transformation, optimization at unprecedented scales, cryptography and data security, molecular simulation for drug discovery, and complex systems modeling for climate prediction. While these opportunities appear transformative, substantial technical challenges remain, including quantum decoherence, hardware scalability constraints, and algorithmic development gaps. The path forward likely involves hybrid quantum-classical architectures, targeted applications in big data analytics, enhanced AI systems, and revolutionary simulation capabilities for complex systems.

International Journal of English Literature and Social SciencesVol. 10(4)
Film Independent (US)
Climate action
Openalex Percentile: Top 9%
Quantum Computing Algorithms and Architecture
2.48
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The Quantum Frontier: How Quantum Computing Will Transform Data Science — Vinu E. Venugopal · International Journal of English Literature and Social Sciences (2025) | TGRS Research Map | TGRS