Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making (2020) / Chapter Skim
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4 2 Data Management Defined Data management is the practice of organizing and maintaining data and data processes to meet ongoing information lifecycle needs. It describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, secure, retrieve, control, share, and purge data.
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5 Figure 1. Data Lifecycle (Spirion, 2019)
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6 □ Data architecture – the overall structure of data and data-related resources as an integral part of the enterprise architecture. □ Data modeling and design – analysis, design, building, testing, and maintenance of data.
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7 and will change too quickly to be handled by traditional database management systems. As such, modern, big data methods to collect, transmit/transport, store, aggregate, analyze, apply, and share these data at a reasonable cost need to be accepted and adopted by transportation agencies if they are to be utilized to facilitate better decision-making.
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8 Table 1. Traditional Data System/Management Approach Contrasted with Modern, Big Data System/Management Approach Characteristics Traditional Data System/Management Modern, Big Data System/Management 1 System Design Systems are designed and built for a predefined Systems are designed and built for many and unexpected purpose; all requirements must be pre-determined vs purposes; constant adjustments are made to the system before development and deployment.
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