This guide aims to equip organizations with a clear, actionable roadmap to establish robust data governance frameworks that enable successful artificial intelligence (AI) adoption. By following the steps outlined, readers will learn how to ensure data quality, security, and accessibility while addressing the unique challenges of governing AI
Cybercrime has increased by 175% since 2022. This highly vulnerable digital landscape is a wake-up call for businesses to be more intentional about data security measures. Organizations cannot undermine the importance of protecting their operations, especially as cybercriminals become more tech-efficient. This article outlines five best practices
The treacherous, binary ways of open-source software have switched courses over time. On the one hand, the percentage of open-source malware intrusions has gone down. However, the number of incidents where developer secrets and other sensitive information have leaked has increased by 12% . For B2B companies, one data breach can result in
The healthcare industry stands at a critical crossroads as cybersecurity emerges as both a formidable challenge and a game-changing opportunity, with recent events underscoring the urgency of this issue. The Columbia University data breach in 2025, which exposed the sensitive information of nearly 870,000 individuals, serves as a chilling reminder
Setting the Stage for AI and Data Quality Imagine a multinational corporation launching an AI-driven customer service platform, only to discover that biased data leads to inappropriate responses, tarnishing its reputation overnight. This scenario underscores a pressing reality: the integration of artificial intelligence into business operations
Understanding the Intersection of Data Governance and CSR Imagine a world where every corporate claim about sustainability or social impact is met with skepticism due to unverifiable data—a scenario that many stakeholders face today, highlighting the urgent need for trust. In an era where trust is paramount, the convergence of data governance and