Using artificial intelligence to manage IT operations, also known as AIOps, is a trend that has attracted a lot of interest and anticipation in recent years. The challenge in IT operations is to run steady-state operations without disruption as well as support agility" can be rephrased as "IT operations face the challenge of maintaining steady-state operations while also supporting agility [11]. AIOps assists in bridging the gap between the demand for IT operations and the ability of humans to meet that demand. However, it is not easy to apply AIOps in current organizational settings. Data Centralization is a major obstacle for adopting AIOps, according to a recent survey by Cisco [1]. The survey, which involved 8,161 senior business leaders from organizations with more than 500 employees, found that 81% of them acknowledged that their data was scattered across different silos within their organizations. This paper illustrates the topic of data silos, their causes, consequences, and solutions.

翻译：利用人工智能管理IT运维（简称AIOps）是近年来备受关注与期待的趋势。IT运维面临的挑战在于既要维持稳态运行的无中断保障，又要支持敏捷性[11]。AIOps有助于弥合IT运维需求与人类能力满足需求之间的差距。然而，在当前组织架构中应用AIOps并非易事。根据思科[1]近期的一项调查，数据集中化是采用AIOps的主要障碍。这项涵盖来自员工超过500人的组织机构的8,161名资深业务领导者的调查显示，81%的受访者承认其数据分散在组织内部的不同孤岛中。本文阐述了数据孤岛的主题、成因、后果及解决方案。