Data management

Main data management scenarios:

• Creation of corporate service bus

• Creation of corporate data bus

• Creation of common data search and visualization window for connected sources

• Creation of common corporate data streams management center

• Optimization of existing data streams

All heterogenous data sources are united into a common knowledge environment via ontology model.

Any user or app may ask a question within the knowledge environment using enterprise terms. The answer will be generated from different sources and provided in uniform view – thanks to unique set of master data and ontology model.

Data management flow consists of three steps:

• А – data acquisition. Data is retrieved from all existing sources, then classified into ontology model. This model is used to create common master data index;

• В – data analysis. When ontology model description is correct as well as digital twins behavior, it is possible to estimate condition of these twins, built at stage A. This model also allows predicting the difgital twins behavior under different circumstances. The outcome of step B: action plan for digital twins manipulation;

• С – data altering. Plans drawn at stage B are implemented here. All changes get registered. Then process returns to stage A, to collect the updated object status data.