Data Exchange Integration System

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Corporate A would like to achieve "Single Identity" by integrating data and services from multiple subsidiaries.
In order to completely grasp the information context and influence levels scattered throughout the subsidiaries, improving the user experience by "single sign-on", "real-time open cross-unit service", maximize the use of internal compliance data, such as "finding accurate number of physical users, "cross-selling marketing", "flexible access management in various entities".
Many companies want to achieve digital transformation with data integration to improve competitiveness and better user experience. However, as data grows and the organization structure becomes more complex, data is scattered everywhere, such as different departments, subsidiaries, data centers, data warehouses, causing:
  • Inconsistent or incomplete data
  • System integration becomes difficult due to low identification of heterogeneous data
  • Inaccurate pooling analysis and high cost
  • Access Management is hard to achieve in cross system
  • Data Regulations and the Difficulty of Opening Data
Unlike most systems that are constantly integrated with the development of middleware, FST Network are:
  • Provides software to record the "event" and "tag" rules associated with data in the global data network at the protocol layer, rather than systems with different rules and formats.
  • The data in each system can be de-identified and registered in the global network with a unique digital identity (UUID). Through tagging, the data is given various auxiliary meanings such as "attributes", "Metadata", "key certificates", " Behavior information” and so on.
  • You can set "Find Logic" to filter real-time and precise data to find data that is worth using and analyzing. For example, locate data with specific attributes, a specific number of tags, or events within a certain time period. Its cryptography and unified time stamp ensure that when integrating cross-systems, the tags are not tampered with and maintain a uniform timing basis, and the traceability of data events is implemented in the data trajectory across the system.
  • Real-time Data Mapping
  • Data Consistency
  • Data Alignment & Settlement
  • Accurate Data
  • Eliminate Unnecessary Data Warehouse
  • Continuous Data Privacy Compliance
  • Continuous Data Protection
  • Optimise efficiency of troubleshooting
  • BI Extension

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