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The significant risk associated with poor Data Lifecycle Management primarily lies in increased data redundancy and inefficiency. When organizations do not effectively manage their data throughout its lifecycle—from collection through active use to deletion—they may end up duplicating data unnecessarily. This redundancy not only occupies extra storage space but can also lead to inconsistencies in data accuracy, making it difficult to maintain a single source of truth.

Additionally, inefficiencies can arise from the inability to locate, access, or analyze relevant data quickly, leading to wasted resources and increased operational costs. Without a structured approach to managing data, organizations might find it cumbersome to follow data governance protocols, thus complicating data retrieval and utilization processes. This ultimately hinders the ability to derive actionable insights from data, which is critical for informed decision-making and strategic planning.