Gaining control over AI governance starts with understanding how enterprise data is accessed and used. Visibility into the ...

In AI deployments, the largest enterprises are interested in protecting their proprietary data and favoring open AI models ...

Unified metadata models are emerging as a cornerstone in the changing landscape of data management, highlighting the critical need for integrated frameworks that ensure data accessibility, security ...

McKinsey''s 2025 global AI survey found that nearly two-thirds of organizations had not yet begun scaling AI across the ...

Opinions expressed by Digital Journal contributors are their own. Anil Lokesh Gadi, a distinguished expert in the fields of advanced data engineering, data analytics, and data warehousing, has ...

Most data governance models weren’t built for AI. They were designed to ensure compliance, not to support real-time decision-making. They helped manage audits and reports but were never intended to ...

Artificial intelligence (AI) is transforming industries by automating processes, enabling smarter decisions, and unlocking new avenues for innovation. According to recent Semarchy research, 74% of ...

In today’s rapidly evolving digital landscape, the value of data cannot be overstated. Data has become the lifeblood of innovation, driving decisions, shaping industries, and transforming how we live ...

A strong data management system is essential for accelerating artificial intelligence-powered medical breakthroughs while ...

More than any other factor, the hyperabundance of accessible data has powered today’s surge in AI adoption and generative AI capability. Collecting, cleaning, organizing, and securing that data for AI ...

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Data governance is an umbrella term encompassing several different disciplines and practices, and the priorities often depend on who is driving the effort. Chief data officers, privacy officers, ...