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...
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...
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...
Key Takeaways: Data enrichment is the process of appending your first-party data with contextually rich third-party data, enabling you to make more data-driven decisions. Traditionally, data...
Key Takeaways: Siloed communication channels can result in inconsistent messaging across departments. Define a digital strategy around customer needs to create a foundation for unifying...
Key Takeaways: Harness automation and data integrity unlock the full potential of your data, powering sustainable digital transformation and growth. Data and processes are deeply interconnected....
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: Automation adoption is gaining momentum as a core component of digital transformation strategies – but integration and multi-dimensional complexity remain top challenges. Most...
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...
