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Peer Incite: Grant, a Sr. Storage Admin at a large bank discusses how heterogeneous storage virtualization can help reduce the budget for 2009.

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Wikitip

Functionality Set - Managing Unstructured Data Across the Enterprise

Organizations should begin to plan for the development of a baseline for future state functionality needed to effectively manage and tame the growth of unstructured data. This conclusion was borne out at the July 28 Peer Incite Research Meeting where Wikibon members, including four practitioners working in three highly regulated industries, energy, finance and healthcare discussed the primary barriers to implementing successful IM initiatives. See also Strategic IM Roadmap

A Baseline

This conclusion requires action from both users and vendors to specify, build, test and deliver a future state information management architecture and related functionality. The right approach is to think about functionality and automation requirements across technology platforms (e.g., storage, messaging, desktop, file servers, content repositories, policy engines, security servers, user directories, portals, and cloud) in the context of a strategic information management framework . There are nine (9) primary categories of functionality that must be considered at a minimum:

  • Policy and Rules Management- functions for creating, maintaining, and enforcing information management policies, whether imposed by jurisdictional law and regulation, internal policy and process, or business agreements. Policy and rules management should operate across technology platforms and act as the center post of information management. Examples include policies for retention, disposition, information assurance, use, and distribution.
  • Content Management – functions for enabling policies for creating, templating, capturing, storing, version managing, retaining, disposing, collaborating, holding and preserving information,
  • Configuration Management – functions for maintaining the overall blueprint of the information management environment - establishing ownership and custodial responsibilities and business application dependencies,
  • Declaration and Classification – functions for enabling policies for the declaration and classification of data, including the ability to distinguish between business records and non-business information, and classifying information based on policy attributes,
  • Crawling and Collecting- functions for locating and gathering unstructured information scattered across the information management environment,
  • Information Access and Discovery – functions for unified indexing, searching, and discovery,
  • Creation and Copy Management- functions that enable rules governing the creation of information, copies to be maintained, and the de-duplication or single instancing of information,
  • Information Assurance –functions for enabling policies for identity management, information authentication, access management, privacy control, use management and auditing. For example, this functionality allows the user to determine the authenticity of business records and to establish and maintain a policy based relationship between users and data,
  • Analytics and Reporting – functions for monitoring, alerting, and real-time reporting on key information management events such as policy updates, configuration changes, security anomalies, classification events, and hold requests.

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Featured Case Study

Virtualization Energizes Cal State University

John Charles is the CIO of California State University, East Bay (CSUEB) and Rich Avila is Director, Server & Network Operations. In late 2007 they were both looking down the barrel of a gun. The total amount of power being used in the data center was 67KVA. The maximum power from the current plant was 75kVA. PG&E had informed them that no more power could be delivered. They would be out of power in less than six months. A new data center was planned, but would not be available for two years.

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Storage Professional Alerts


Featured How-To Note

Storage Virtualization Design and Deployment

A main impediment to storage virtualization is the lack of multiple storage vendor (heterogeneous) support within available virtualization technologies. This inhibits deployment across a data center. The only practical approach is either to implement a single vendor solution across the whole of the data center (practical only for small and some medium size data centers) or to implement virtualization in one or more of the largest storage pools within a data center.

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