More and more data is being created in the world of today, especially machine-generated data (MGD). Industry awareness is rising on how to define data, how to manage and store it and how to make use of it.
This enormous growth of data poses significant challenges; e.g.
- Smart, efficient and affordable information analysis
- Ensuring data quality, data management, data policies and data risk management
- Design effort to cope with the data growth
High tech industry is seeking for opportunities to use MGD efficiently. New business options are being explored (e.g. new services based on e.g. data mining techniques), better control of business processes, more efficient development, etc. Another important trend is the fact that the context of systems is strongly increasing in importance. This trend, also seen in the general move towards information-centric systems-of-systems, has significant consequences for systems design, development, operation, and their role in business in general.
The MaGenTa 2013 project focused on data distribution architectures (important for system optimization and necessary for improvement of system interface design), data modelling (important in system-to-system communication), and data governance. The project goals were as follows:
- Intra- and inter-system data architecting in complex data-intensive system of systems
- Data-flow design with emphasis on effective data utilization and system interoperability
- Development of methods for data- and information modelling and integration in the design process
- Methods for data governance (control, data quality, work-flow, data policies).
The MaGenTa project was the start of a successful TNO-ESI program on analysing and optimizing systems in their context on basis of machine-generated data (and successively context-derived data). All key Dutch high-tech industry is exploring methods and tools to analyse the operational context of their systems and to optimize their systems in such context. Magenta 2013 has brought data awareness to a next level as it has structured the ASML data-awareness in areas such as data distribution, data models, data access, data policies, and data governance. The results of Magenta 2013 formed the basis of a range of data-related optimization activities, especially on data modelling.
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