Key Takeaways: Interest in data governance is on the rise – 71% of organizations report that their organization has a data governance program, compared to 60% in 2023. Top reported benefits of data...
Large Language Models (LLMs) became popular after the release of ChatGPT two years ago. The idea of chatting with an AI through a browser significantly reduced the technical barriers, making LLMs the...
Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity...
Key Takeaways: MDM delivers a unified holistic view of your data across domains, so you can make faster, more accurate decisions. Challenges around data literacy, readiness, and risk exposure need to...
Key Takeaways: Data quality is the top challenge impacting data integrity – cited as such by 64% of organizations. Data trust is impacted by data quality issues, with 67% of organizations saying...
Key Takeaways: Data mesh is a decentralized approach to data management, designed to shift creation and ownership of data products to domain-specific teams. Data fabric is a unified approach to data...
This year, our annual Data Integrity Summit, Trust ’24, was better than ever – and a big part of what made the event so exciting was our first-ever Data Integrity Awards! We were thrilled to...
Key Takeaways: Only 12% of organizations report their data is of sufficient quality and accessibility for AI. Data analysis (57%) is the top-cited reason organizations are considering the use of AI....
Key Takeaways: Trusted AI requires data integrity. For AI-ready data, focus on comprehensive data integration, data quality and governance, and data enrichment. A structured, business-first approach...
