37.2 Outlook
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
Figure 36.2 Dynamic framework for social change
Figure 36.3 Synthesis of recommendations in part II
It is often said that “data is the new oil”. It is hard to figure out with any certainty who wrote about this metaphor first. A cursory search on Google suggests it was used originally in an article by The Economist [Par17] with many authors following suit by describing why, for all practical reasons, data is not the new oil (e.g. [Mar18]). Whatever the practical implications, the metaphor at least illustrates that data is an important business asset that deserves to be managed as such. This is the field of data management (or DM for short). See also sidebar 1.
Sidebar 1. Interview with Marco van der Winden (Summer 2019)
My experience is that the importance of data is underestimated in the way that there was/ is no primary focus on it. Living in the low countries where there is an abundance of water, data is mostly seen as something that can be easily be obtained, just like water. To continue the comparison, the Dutch are very good with containing the water streams and keeping the seawater outside with dikes. But with data we are less experienced. We let data sometimes uncontrollably flow though our fields without knowing where it goes or even why we are doing it.
We
