Big Data Technologies for Future Digital Transformation and Innovation

Francesco Schiavone

Big Data Technologies for Future Digital Transformation and Innovation

Author(s)	Francesco Schiavone
Country	Italy
Abstract	Big data technologies have emerged as a fundamental driver of digital transformation and technological innovation across contemporary organizations and industries. The rapid expansion of connected devices, cloud platforms, artificial intelligence, Internet of Things ecosystems, digital services, and real-time information systems has created unprecedented volumes of structured, semi-structured, and unstructured data. Conventional data-processing approaches are increasingly insufficient for managing such information at scale, creating a growing need for advanced technologies capable of storing, processing, analyzing, and transforming data into actionable knowledge. This study examines the role of big data technologies in supporting future digital transformation and innovation, with particular attention to distributed computing, cloud-based analytics, artificial intelligence, machine learning, Internet of Things technologies, edge computing, data visualization, and intelligent decision-support systems. A qualitative descriptive research design based on secondary scholarly literature was employed. Thematic analysis was used to identify major technological capabilities, innovation outcomes, implementation requirements, and emerging challenges associated with big data-driven transformation. The findings indicate that big data technologies can improve organizational agility, operational efficiency, predictive capability, customer intelligence, resource optimization, and innovation performance. Distributed data-processing technologies enable organizations to manage large-scale datasets, while cloud computing provides flexible infrastructure for analytical workloads. Artificial intelligence and machine learning further convert complex data into predictive and prescriptive intelligence, supporting faster and more informed decisions. Edge computing and Internet of Things technologies extend analytical capabilities closer to data-generation points, enabling responsive and real-time applications. However, implementation is affected by challenges related to data quality, cybersecurity, privacy, interoperability, computational requirements, technological complexity, skills shortages, and governance. The study concludes that future digital transformation will increasingly depend on integrated big data ecosystems rather than isolated technologies. Successful adoption requires scalable infrastructure, responsible data governance, continuous innovation, human expertise, and strategic alignment between technological capabilities and organizational objectives.
Keywords	Big Data, Digital Transformation, Technological Innovation, Cloud Computing, Artificial Intelligence, Machine Learning, Internet of Things, Edge Computing, Data Analytics, Digital Innovation.
Field	Engineering
Published In	Volume 1, Issue 6, November-December 2019
Published On	2019-11-18

View / Download PDF File

About AIJARD Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+1-872-302-3851	editor@aijard.com

American International Journal of Advanced Research and Development

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Big Data Technologies for Future Digital Transformation and Innovation

Share this