This episode of Techsplainers examines data fragmentation—the widespread problem of organizational data scattered across different systems, applications, clouds, and documents. We explore the five key warning signs of fragmentation: absence of a single source of truth, excessive manual work, stagnant decision-making, rising IT costs, and security gaps. The discussion highlights how fragmented data creates significant barriers to enterprise AI adoption by slowing execution, limiting context, and increasing risk. We identify the main culprits behind fragmentation, including hybrid multicloud environments, disconnected systems, growing data volumes, and weak governance. Finally, the episode outlines practical solutions that don't require consolidating all data into one place, including cultural shifts, stronger governance, strategic consolidation, integration approaches, data fabric architectures, and AI-powered automation tools. For organizations looking to accelerate AI initiatives and improve decision-making, addressing data fragmentation is an essential first step.

Find more information at https://www.ibm.com/think/topics/data-fragmentation

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Narrated by Dan Segal