Portal:Storage
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The Wikibon Data Storage Portal contains data storage industry research, articles, expert opinion, case studies, and data storage company profiles. | The Wikibon Data Storage Portal contains data storage industry research, articles, expert opinion, case studies, and data storage company profiles. | ||
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| - | ![[Image:LinkedIn.gif | + | '''Latest Information Storage Research''' |
| - | |[[Image:facebook.jpeg | + | * [http://wikibon.org/wiki/v/Storage_Facts%2C_Figures%2C_Best_Practices%2C_and_Estimates Storage Facts, Figures, Best Practices, and Estimates] |
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[[Storage virtualization design and deployment | read more...]] | [[Storage virtualization design and deployment | read more...]] | ||
| - | |} | + | |}[[Category:Backup and restore]][[Category: Blade computing]][[Category: Business compliance]][[Category: CDP]][[Category: Careers]][[Category: Careers wikitips]][[Category: Clustered storage]][[Category: Compliance and discovery]][[Category: Enterprise mobile wikitips]] |
Current revision as of 00:18, 23 February 2010
The Wikibon Data Storage Portal contains data storage industry research, articles, expert opinion, case studies, and data storage company profiles.
Latest Information Storage Research
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| >>Join our Group | >>Become a Fan | >>Follow @Wikibon | >>Read the Blog | ||||
WikitipEDiscovery Pricing EstimationOrangeLT™’s Predictive Pricing Estimator is an online predictive pricing estimation tool designed to help law firms, corporations, and governmental agencies estimate, compare, and evaluate the monetary costs associated with the use of analytics, processing, and review services in the conduct of electronic discovery. Using a combination of industry-accepted volume and cost parameters, the Predictive Pricing Estimator allows users to enter estimates for both the volume of data and potential reviewers available and to see how these estimates influence data reduction and review costs throughout the electronic discovery stages of analytics, processing, and review. How can organizations use the estimator to engage with OrangeLT™? While Predictive Pricing Estimator results are not legally binding estimates, organizations can use the calculated results of estimations to help develop Request for Proposals (RFPs) and Statement of Work (SOW) documents that may be used in developing and implementing their electronic discovery project plans. How can users access the Predictive Pricing Estimator? To access the Predictive Pricing Estimator, simply visit: OrangeLT Action Item: eDiscovery is a volume-driven activity-- more volume equals higher costs. Typically reactive approaches to legal edicts are executed without a clear eye on costs. This approach is unsustainable as volumes grow unabated. Tools such as the Predictive Pricing Estimator can help ease the near-term pain. Longer term, however, users must develop information management architectures that deal with the root problem, namely shoving all data in a central archive with limited classification capabilities that is a dead end. Footnotes: |
Featured Case Study
Virtualization Energizes Cal State UniversityJohn 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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Featured How-To Note |
Storage Virtualization Design and DeploymentA 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. | |||
