Executive Summary (TL;DR) CDOs can no longer ignore the potential of archived data in driving AI initiatives. Fragmented archives create challenges in governance, compliance, and analytics. Transforming archived data into a unified, AI-ready asset can significantly reduce costs and risks. See how a top-5 US bank achieved this — download the case study. What Breaks […]
Executive Summary (TL;DR) Legacy applications can cost IT teams millions in technical debt. Proactive application retirement is essential for optimizing budgets and ensuring business continuity. Implementing a structured approach can yield rapid ROI and improved efficiency. The full Ultimate Guide to Application Retirement is available in our resource library. What Breaks First: A War Story […]
Executive Summary (TL;DR) Application rationalization frameworks are critical to distinguishing valuable applications from those that should be retired, thereby enhancing operational efficiency. Failure to implement a structured approach can lead to silent failures, where outdated applications create hidden costs and risks. Frameworks must integrate governance, compliance, and technical considerations to ensure a strategic approach to […]
Executive Summary (TL;DR) Application modernization services encompass various strategies including retiring, replatforming, or rebuilding legacy applications to enhance efficiency and reduce operational costs. Most organizations struggle with decision-making, often misjudging the implications of modernization approaches, leading to wasted resources and stalled progress. Understanding the specific constraints and failure modes associated with legacy systems is crucial […]
Executive Summary (TL;DR) AI in manufacturing is transformative but requires high-quality data. Generative AI capabilities extend far beyond simple chatbots into predictive maintenance and quality assurance. Effective Customer Data Platforms enhance AI outcomes by integrating IoT, CRM, and ERP data. The full guide, 5 Things You Need to Know About AI in Manufacturing, is available […]
Executive Summary (TL;DR) AI hallucinations can compromise decision-making and lead to significant business risks. Effective data governance is essential for ensuring high-quality, reliable data inputs into AI systems. Implementing a governed data pipeline and robust metadata management are critical steps for AI success. The full framework for implementing these strategies is available in our Enterprise […]
