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 ...

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, ...

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 ...

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 ...

As enterprises rush to deploy copilots, generative AI platforms, and automated workflows, many security teams remain focused ...

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 ...

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 ...

The COVID crisis has shown that ethical and effective uses of data and increased sharing of data can save lives and can be critical for society as a whole (by contrast to the use of data made by ...

As AI adoption accelerates, organizations will increasingly measure AI success not by model size, but by the economics of ...

While it’s important to implement processes and procedures that safeguard data security and privacy, you can also focus on more strategic data governance goals. An organization’s data is one of its ...

The advantage AI will not be won by organizations that deploy the most tools; it will go to organizations that can see ...