Key data and analytics trends in 2026 include decision intelligence, real-time analytics, semantic layers, platform ...

To adopt AI responsibly, organizations must understand the high-stakes risk profile of video data and take concrete steps to ...

In 2026, data governance has stopped tiptoeing around the edges of organizational strategy and stepped directly into the ...

Computational intelligence is increasingly embedded in the operational architecture of counterterrorism, civic surveillance, and public safety. Its deployment across jurisdictions reveals deep ...

In the ever-evolving landscape of data management and utilization, it's crucial to address the prevailing myth that data governance and master data management (MDM) are disciplines strictly reserved ...

Operational Data Modeling Some of the most meaningful operational action derived from data governance stems from data modeling. The interchange of data between varying systems as part of a collective ...

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 ...

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 ...

Most enterprises assume their governance systems are built for modern risk. Policies are mature. Controls are defined. Programs are resourced. Yet beneath ...

Back in 2006, British mathematician Clive Humby stated that data was the new oil. Like oil, data isn’t useful in its raw state and must be refined, processed, and distributed to deliver value. Nearly ...