AI-Powered Data Platforms for Digital Transformation
Keywords:
AI-Driven Data Platforms, Cloud Data Architecture, Data Acquisition Systems, Data Governance Frameworks, Real-Time Data Analytics, Streaming Data Processing, Data Quality Management, Semantic Data Integration, AI Data Preparation, Enterprise Data Platforms, Digital Transformation Systems, Data Science Environments, Scalable Data Infrastructure, Cross-Domain Data Integration, Data Platform Performance Metrics, Risk and Governance in Data, Intelligent Data Pipelines, Cloud-Native Data Systems, Data-Driven Enterprises, Integrated Analytics Platforms.Abstract
Digital transformation refers to the strategic adoption of digital technologies to create or redesign business processes, customer experiences, and operations in response to evolving market demands. Achieving this transformation requires alignment across business operations, technology adoption, organizational culture, and communication strategy. AI-driven cloud data platforms serve as a critical enabler of this alignment, unifying data acquisition, governance, storage and management, analytics, and data science environments within a single cloud-based architecture.
This study formalizes an architecture for AI-driven cloud data platforms through a rigorous analysis of relevant technologies. It examines semantics-based data acquisition and integration techniques alongside AI capabilities for data preparation, quality assurance, real-time analytics, and stream processing, illustrating their application across commerce, manufacturing, finance, and other domains. The proposed framework contributes a comprehensive definition of AI-driven cloud data platforms, credible performance metrics, an industry-agnostic structure applicable across sectors, and a risk-and-governance perspective essential for enterprise adoption.
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