IBM内部信息转型

J. A. Vayghan;S. M. Garfinkle;C. Walenta;D. C. Healy;Z. Valentin
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引用次数: 28

摘要

将数据用作企业资产的能力是每一项企业转型计划的核心。这种能力对于在整个企业中一致地重用数据并从中获得可操作的知识至关重要。准确和高质量的数据必须在整个企业内一致地传播意义和价值,并遵守企业的政策和流程。由于各种原因,大型企业在本地级别管理数据(例如,针对每个部门和地点),导致信息“筒仓”,数据被冗余地存储、管理和处理,每个仓库都有自己的策略和流程,从而导致不一致。IBM已经开始了一个转型过程,以建立一个管理其关键数据的程序,从创建与IBM业务战略一致的企业数据战略开始。在本文中,我们描述了迄今为止IBM转型过程的进展。我们专注于IBM卓越企业业务信息中心(EBI-CoE)的活动,该中心负责建立、实施和部署企业数据架构计划。EBI-CoE使用IBM及其合作伙伴的前沿信息管理技术和服务来应对企业数据挑战。我们介绍了从这一持续的内部转型过程中获得的经验教训和最佳实践,这些经验教训和实践对在转型运营和业务模式时面临类似数据挑战的企业非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The internal information transformation of IBM
The ability to utilize data as an enterprise asset is central to every enterprise transformation initiative. This ability is critical for reusing data consistently throughout the enterprise and deriving actionable knowledge from it. Accurate and high-quality data must consistently propagate meaning and value throughout the enterprise and comply with the policies and processes of the enterprise. For a variety of reasons, large enterprises manage data at a local level (e.g., for each department and location), resulting in information “silos” where data is redundantly stored, managed, and processed, each with its own policies and processes, leading to inconsistency. IBM has begun a transformation process to establish a program for the management of its critical data, beginning with the creation of an enterprise data strategy that is aligned with IBM business strategy. In this paper, we describe the progress, to date, of the IBM transformation process. We focus on the activities of the IBM Enterprise Business Information Center of Excellence (EBI CoE), which is responsible for establishing, implementing, and deploying the enterprise data architecture program. The EBI CoE uses leading-edge information management technology and services from IBM and its partners to address enterprise data challenges. We present lessons learned and best practices derived from this ongoing internal transformation process that can be useful for enterprises facing similar data challenges as they transform their operations and business models.
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