Safeguarding digital societies: The convergence of data engineering and cybersecurity

Data engineering and cybersecurity convergence have become essential for protecting sensitive information in our hyperconnected world. As organizations face increasingly sophisticated cyber threats, traditional security approaches prove insufficient. This article explores how advanced data engineering practices transform cybersecurity through real-time threat detection, big data analytics, regulatory compliance solutions, and emerging technologies. By leveraging sophisticated data pipelines, machine learning algorithms, graph databases, and analytics platforms, organizations can identify and neutralize threats before they cause significant damage. The integration of these technologies enables faster detection times, reduced false positives, and more efficient incident response. From Zero-Trust architectures to federated learning, quantum-safe cryptography, and edge computing security, data engineering continues to reshape how organizations approach cybersecurity, making it a foundational element for effective defense strategies in an increasingly uncertain digital landscape.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-04-12
DOI
https://doi.org/10.30574/wjarr.2025.26.1.1119
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Safeguarding digital societies: The convergence of data engineering and cybersecurity

Ashish Chandra
World Journal of Advanced Research and Reviews
Big Data Technologies and Applications
article

Safeguarding digital societies: The convergence of data engineering and cybersecurity

Ashish Chandra
article en

Abstract

Data engineering and cybersecurity convergence have become essential for protecting sensitive information in our hyperconnected world. As organizations face increasingly sophisticated cyber threats, traditional security approaches prove insufficient. This article explores how advanced data engineering practices transform cybersecurity through real-time threat detection, big data analytics, regulatory compliance solutions, and emerging technologies. By leveraging sophisticated data pipelines, machine learning algorithms, graph databases, and analytics platforms, organizations can identify and neutralize threats before they cause significant damage. The integration of these technologies enables faster detection times, reduced false positives, and more efficient incident response. From Zero-Trust architectures to federated learning, quantum-safe cryptography, and edge computing security, data engineering continues to reshape how organizations approach cybersecurity, making it a foundational element for effective defense strategies in an increasingly uncertain digital landscape.

World Journal of Advanced Research and ReviewsVol. 26(1)
Openalex Percentile: Top 92%
Big Data Technologies and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.