Main Definition
Data sprawl is the uncontrolled spread of data across storage systems, clouds, and devices, creating visibility gaps, risks and hidden costs. Data sprawl happens when an organization’s data spreads across many storage locations- multiple clouds, on-premises storage, SaaS applications – without a consistent way to see, track, and protect it. Data sprawl is unintentional. However, it prevents organizations from realizing the full value of their data and can put security at risk.
The problem hits hardest with unstructured data: files, documents, images, and research outputs that make up the majority of enterprise data. Unstructured data lacks the built-in organization of databases. In research and HPC environments, data sprawl can reach extreme scale as scientific workflows and research efforts generate outputs across multiple file systems. Fixing it requires first and foremost, a strategy for data observability. IT leaders need a vendor neutral solution that allows them to see all their data across multiple storage systems. Implementing a metadata-driven data catalog that can classify data across vendors and platforms is the first step to eliminating sprawl and starting to understand where valuable data lives.
Starfish’s Unstructured Data Catalog is the antidote to data sprawl, giving you complete visibility to your data across all your file systems, regardless of how many on-premises or cloud locations you are accessing. By giving you a complete, continuously updated map of your data, it provides the starting point for consolidating, organizing, protecting, and optimizing how project data is stored.
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