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  • Data Space Pathway - Data oriented challenge dimensions

Data Space Pathway - Data oriented challenge dimensions

Mapped projects (1)
Mapped results (1)
  • DS Pathway - Data management levels
    (1)
    (1)
    • No Data Management Culture in the company
    • Data stored in Enterprise Application and managed from there
    • Cross application Data Management Bridges
    • Common set of data management application applied to data Source and Enterprise Application
    • Data Management Application used to assign a value to data
      (1)
      (1)
  • DS Pathway - Data protection levels
    • No specific Data Protection measures in place regarding storage, computation and transfer of data
    • Each single Enterprise Application (ERP SCM PLM) is responsible for Data Protection
    • Secure Data Bridges between silos implemented on a case-by-case basis
    • Common Data Protection mechanisms and tools are shared at company level and used in every application
    • Data Protection mechanisms associated to Data Spaces increase the value of Data
  • DS Pathway - Data Processing Architecture Implementation Levels
    (1)
    (1)
    • Data not processed or processed by default procedures out of control for the company
    • Data processed inside Enterprise Applications (ERP SCM PLM) according to architectures and tools predefined by them
    • Data Processing architectures (embedded, edge, cloud) implemented for ad-hoc data bridges in Enterprise Applications
    • Common Data Processing architecture adopted for all Enterprise Applications, both Data at Rest and Data in Motion
    • Data Processing tools associated as a service to Data Sets, increasing value in the Data Space and implementing Data Economy services
      (1)
  • DS Pathway - Data Visualisation and User Interaction
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    (1)
    • Data visualisation tools not implemented or implemented by third parties out of control of the company
    • Data visualisation tools embedded in Enterprise Applications on top of predefined sets of Data
    • Data visualisation applications are developed ad-hoc cross-silos to show data coming from different sources
    • Common agreed repository of Data Visualisation tools is shared in the company, at disposal for any application
    • Data Visualisation tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services
      (1)
  • DS Pathway - Ecosystems for Data Sharing
    • Data Sharing not implemented or implemented without any control
    • Data Sharing from different sources implemented for specific suppliers and customers
    • Data Sharing allowed from inside Enterprise Applications to a predefined value ecosystem
    • A common and agreed architecture for secure and sovereign Data Sharing implemented
    • Data Sharing applications associated as a service to available Data Sets, increasing value in the Data Space and implementing Data Economy services
  • DS Pathway - Data Analytics Implementation Levels
    (1)
    (1)
    • Data analytics not performed or performed by third parties out of control of the company
    • Data Analytics procedures implemented (and replicated) from inside Enterprise Applications only
    • Data Analytics procedures implemented across silos in an ad-hoc fashion
    • Common repository of Data Analytics tools is shared in the company, at disposal for any application
    • Data Analytics tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services
      (1)
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