Читать книгу Data Management: a gentle introduction - Bas van Gils - Страница 10
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Figure 2.1 Fact, data, information and intelligence
Figure 4.1 Positioning data management
Figure 4.2 From architecture to a more “detailed design”
Figure 4.3 The Cynefin framework, based on [SB07]
Figure 9.1 Data Governance & Data Management (Taken from [Hen17])
Figure 9.2 Data governance model
Figure 13.1 Data virtualization
Figure 13.2 Introducing a “hub” to reduce the number of connections between systems
Figure 18.1 Typical BI architecture, from source systems to end-users
Figure 18.2 Example BI architecture, including self-service
Figure 19.1 Big data adoption (taken from [Agr19] and based on research by Dresner Advisory)
Figure 19.2 Example big data architecture
Figure 20.1 Balancing DM offense and defense with people, process, (meta)data, and technology
Figure 23.1 System dynamics model as input for a business case
Figure 25.1 Stewardship models, inspired by [Pol13]
Figure 25.2 Publishing an overview of data owners and data stewards
Figure 27.1 Position of policies
Figure 28.1 Concepts in context
Figure 29.1 Metadata from different sources
Figure 32.1 (Cluster of) security use case(s)
Figure 32.2 Visualizing impact of security measures
Figure 33.1 Structure of the SFIA framework
Figure 34.1 Start-up, scale-up, benefits
Figure 35.1 TOGAF’s Architecture Development Method (taken from [The11])
Figure 35.2 Benefit realization diagram
Figure 35.3 Business blueprint
Figure 35.4 Capability analysis
Figure 35.5 Portfolio analysis
Figure 36.1 Balancing data management offense and defense, theory and practice
