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It’s a given in this digital age that enterprise data—and unstructured file data in particular—continues to grow. It’s also clear that, for many, this data continues to be in more places—the modern organization is typically highly distributed. And if the organization is highly distributed, so is its data. |
在这个数字时代，企业数据，尤其是非结构化文件数据，持续增长是理所当然的。同样显而易见的是，对于许多人来说，这些数据继续存在于更多的地方——现代组织通常是高度分散的。而且，如果组织高度分散，那么其数据也是高度分散的。 |
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This ‘data entropy’ creates challenges around cost effectively and securely storing, protecting, and accessing this data, especially for unstructured data sets that might be highly collaborative in nature. Indeed, research from Enterprise Strategy Group found that locating the right data set and making it accessible in a timely fashion was the top file storage-related data challenge that organizations are facing.1 Number two on that list are challenges associated with the management, optimization, and placement of data across separate locations. |
这种 “数据熵” 给以经济实惠和安全的方式存储、保护和访问这些数据带来了挑战，尤其是对于本质上可能具有高度协作性的非结构化数据集而言。事实上，Enterprise Strategy Group的研究发现，找到正确的数据集并使其及时访问是组织面临的最大文件存储相关数据挑战。1 该清单上的第二大挑战是与管理、优化和在不同位置放置数据相关的挑战。 |
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For many, these challenges are becoming more profound. Understanding and managing large unstructured data volumes across many locations and users is complex, and this complexity can drive up costs—both physical storage costs but also management overhead, such as service desk costs, as data volumes, locations, and users grow. There are also potentially significant risks associated with such data sets; files often contain highly sensitive data—customer data, personally identifiable information, financial information, or intellectual property—that could have major business impacts if it fell into the wrong hands—either by malicious or accidental means. |
对许多人来说，这些挑战正变得更加深刻。了解和管理跨多个位置和用户的大量非结构化数据非常复杂，随着数据量、位置和用户的增长，这种复杂性会推高成本，包括物理存储成本，还会增加管理开销，例如服务台成本。此类数据集还存在潜在的重大风险；文件通常包含高度敏感的数据（客户数据、个人身份信息、财务信息或知识产权），如果这些数据落入坏人之手，无论是通过恶意还是意外手段，可能会对业务产生重大影响。 |
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A key issue is that storage and data management tools have not kept pace with the realities of an accelerating file data environment. Enterprise Strategy Group’s research also identified a lack of automation in file data management as a major challenge in this respect. As organizations continue to adopt new and emerging technologies—particularly advanced AI use cases that are built on unstructured data sets—we can expect they will seek more powerful capabilities that let them not only manage their growing volumes of file data with more intelligence and at a granular level, but also by using automation to streamline the process. |
一个关键问题是存储和数据管理工具跟不上文件数据环境加速的现实。企业战略集团的研究还发现，文件数据管理缺乏自动化是这方面的主要挑战。随着组织不断采用新的和新兴的技术，尤其是基于非结构化数据集的高级人工智能用例，我们可以预期他们将寻求更强大的功能，使他们不仅能够以更智能和更精细的级别管理不断增长的文件数据，还可以使用自动化来简化流程。 |
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1. Source: Enterprise Strategy Group Research Report, Navigating the Cloud and AI Revolution: The State of Enterprise Storage and HCI, March 2024. |
1。来源：企业战略组研究报告，《驾驭云和人工智能革命：企业存储和超融合基础架构现状》，2024年3月。 |