Guidebook for Managing Data from Emerging Technologies for Transportation (2020) / Chapter Skim
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Pages 5-10
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From page 5... ...
5 Data governance deals with quality, security and privacy, integrity, usability, integration, compliance, availability, roles and responsibilities, and overall management of the internal and external data flows within an organization (Roe 2017)
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6 Guidebook for Managing Data from Emerging Technologies for Transportation Table 1 contrasts 11 characteristics of traditional data management practices with their modern big data system/management counterparts. The table provides examples that demonstrate the stark contrast between the current state of the practice for most transportation agencies and the ideal state based on data industry best practices.
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Characteristics Traditional Data System/Management Modern Big Data System/Management 1 System Design Systems are designed and built for a pre-defined purpose; all requirements must be pre-determined before development and deployment. versus Systems are designed and built for many and unexpected purposes; constant adjustments are made to the system following deployment.
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8 Guidebook for Managing Data from Emerging Technologies for Transportation the required data sets and data uses and to create optimal data organization (and as such requires compromises in order to satisfy these user/analytical needs)
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Laying the Foundation 9 by a set of policies that enforce a strict and detailed approach to application development and data analysis. In modern data systems, data governance cannot be performed in the traditional way, because it would be too restrictive.
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10 Guidebook for Managing Data from Emerging Technologies for Transportation defined in the model. This is a tedious and complex task.
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