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Semantic Laboratories
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info@semanticlaboratories.com La Jolla, CA |
Service: Review Current Practices
In many organizations, the evolution of informatics systems to support drug discovery research has required ad-hoc solutions that may eventually become data bottlenecks and have data security issues. As the organization evolves, these data processes may need to be reviewed and revisited to support increasing research demands, the need for scalability, increased performance and increased data security.
A thorough review of data practices (performed through interviews and discussions with key research and IT team members) provide an organization with organized documentation of current data practices and a recommendation for areas that could be improved upon to achieve research goals through focused software re-configuration, acquisition or custom software development.
Semantic Laboratories provides a rapid and inexpensive way for an organization to capture and evaluate current data processes before investing in commercial solutions or developing custom in-house solutions. The key benefits to this analysis are:
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provide research and IT management with a snapshot of the current data practices occurring across the organization |
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identify the major bottlenecks occurring in the data and analysis flow from research group to research group |
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identify potential security risks in the current practices |
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assess the disaster recovery mechanisms in place to ensure data recovery |
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assess the current informatics platforms for scalability for future research growth |
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assess the current informatics platforms for operational performance and robustness |
The products of this review include:
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an Inventory Report that includes an inventory and description of current data solutions and data processes across the research organization |
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a Security Report that includes a description of current data security policies implemented |
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a Recovery Report that includes a description of current data backup and recovery mechanisms |
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a Bottleneck Report that identifies current and potential data processing bottlenecks within or a across research groups |
