Logic Operating Centre
What is Logic Operating Centre (LOC) ?
Our data platform, LOC, can help individual data domain personnel (data scientists, data stewards or data owners) to “mesh” inter-connected logic within each data processes as well as creating accurate runtime metadata referencing via our unique data events, which enable organisations to achieve:
Accurate blueprint of data pipelines for entire system
Full-suite flexible access control management
Swift data discovery, catalogue and observability
Cross-systems lineage handling on data processes
Reliable audit-trail capability for compliance & regulatory requirement
FST Network’s LOC Studio also empowers IT users and data teams to interact well with non-technical personnel - enhancing cohesive integration, forming strong data network as well as lowering the barrier-of-entry in coding for the ease of usability and better team collaboration.
Data Event Category & Discovery
Enabling organisations to perform detailed anatomy about its entire data system environment, where precise categorisation and classification about its data and relevant storage can now be accurately labelled and referenced towards its “atomic” level.
LOC also provides powerful visualisation tool for scrupulous discovery as well as meticulous dissection on all its datasets within their systems.
Data Pipeline Building & Deploying
Precise Data Processes curation including its operational and business logic pronouncing relevant event-emitting conditions can be rapidly set up and managed within our LOC Studio's Data Process Interactive Map.
LOC applies easy-to-manage and user-friendly mechanics to empower swift annotation enhancement on individual data processes, to equip them with necessary logic and necessary agents for direct data control and complex data governance management.
Active Runtime Data Lineage
Provisioning of complex source-event-target relations and relevant digital-IDs are available in LOC Studio's Data Discovery Event Repository including respective event properties.
Our event description and relevant labelling highlights straightforward “source-to-destination” data lineage to further enhance the understanding of relevant events unfolding and flow relationships amongst the connecting data points as well as projecting any end-to-end data journey.
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