Trust ’25 Recap: The Latest in AI, Modernization, and Location Intelligence
There’s a special kind of energy that comes from bringing data leaders together with a shared goal: unlocking more value from their data. At Trust ’25, our virtual Data Integrity Summit, that energy was palpable. Data and analytics professionals from around the world joined us to explore what’s next for trusted data – and how […]
AI Advancements Will Solve Your Top Customer Communications Challenges
Customer communications are under pressure – especially in highly regulated industries like financial services, insurance, utilities, and telecom. If you’re a leader in this space, you already know the stakes. Your customers expect seamless, personalized experiences. Your regulators demand compliance. And your teams are stretched thin trying to deliver both, often with outdated systems and […]
Accelerate AI and Analytics with these 4 New Enhancements in the Precisely Data Integrity Suite
Key takeaways: New Data Integrity Suite innovations include AI-powered data quality, and new data observability, lineage, location intelligence, and enrichment capabilities. These enhancements help you scale data quality for AI, boost visibility across hybrid data environments, and embed trusted location data into critical workflows. The Suite ensures you’re able to reduce risk, drive innovation, and […]
From AI Chaos to Control: A Flexible Data Integrity Ecosystem
If you’re leading any kind of AI initiative right now, you already know the opportunities are vast – but so is the complexity. Between widespread generative AI adoption, a wide variety of LLM options, and compelling visions of agentic AI-fueled automation, the pace of innovation is extraordinary. But the fact is this: we won’t get […]
Mastering AI Data Observability: Top Trends and Best Practices for Data Leaders
Key Takeaways: Observability is essential for trusted AI – Yet most organizations lack the structured programs, tools, and cross-team collaboration needed to make it effective. North America is pulling ahead – U.S. organizations show significantly higher observability maturity, trust in AI outputs, and use of diverse data types compared to Europe. Leaders must act now […]
Gartner Data & Analytics Summit Takeaway: “Why is nobody listening?”
Is your data AI-ready? That was a consistent theme at this year’s Gartner Data & Analytics Summit in Orlando, Florida. There were many Gartner keynotes and analyst-led sessions that had titles like: “Scale Data and Analytics on Your AI Journeys” “What Everyone in D&A Needs to Know About (Generative) AI: The Foundations” “AI Governance: Design […]
Better Together: Data Enrichment and AI for Smarter Decision-Making
Key Takeaways Enrich your raw data with context to unlock its full potential and enable smarter, data-driven decision-making. Combine data enrichment and AI for more accurate predictions, personalized insights, and proactive strategies. To successfully implement data enrichment, identify current data gaps, choose the right providers, and leverage APIs and AI for maximum impact. Modern businesses […]
Data Integrity for AI: What’s Old is New Again
Artificial Intelligence (AI) is all the rage, and rightly so. By now most of us have experienced how Gen AI and the LLMs (large language models) that fuel it are primed to transform the way we create, research, collaborate, engage, and much more. Yet along with the AI hype and excitement comes very appropriate sanity-checks […]
Redefining AIOps IT Workflows with Legacy System Visibility
Key Takeaways: Centralized visibility of data is key. Modern IT environments require comprehensive data for successful AIOps, that includes incorporating data from legacy systems like IBM i and IBM Z into ITOps platforms. Predictive of AIOps capabilities will revolutionize IT operations. The shift from reactive to proactive IT operations is driven by AI-powered analysis, automation […]
Mainframe Data Meets AI: Reducing Bias and Enhancing Predictive Power
Key Takeaways: The significance of using legacy systems like mainframes in modern AI. How mainframe data helps reduce bias in AI models. The challenges and solutions involved in integrating legacy data with modern AI systems. The potential benefits of these integrations. In today’s rapidly evolving technological landscape, businesses across industries are constantly looking for ways […]
How to Power Successful AI Projects with Trusted Data
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 to AI is essential. Start with clear business use cases and ensure collaboration between business and IT teams for the greatest impact. Building data literacy across your organization empowers […]
AI Success – Powered by Data Governance and Quality
Key Takeaways: Data integrity is essential for AI success and reliability – helping you prevent harmful biases and inaccuracies in AI models. Robust data governance for AI ensures data privacy, compliance, and ethical AI use. Proactive data quality measures are critical, especially in AI applications. Using AI systems to analyze and improve data quality both […]