advantages of semantic PDM

competent handling of your data

Achieve more leeways in handling your data. 

Defining a sustainable semantic data model for your products and processes puts you onto the driver seat and allows you to analyze and optimize your data a lot easier. 


transparency and traceability

The visualization of query results as a graph creates transparency and guarantees a high user acceptance.


highly optimized processes based on clear definition of terminology and data ownership

Working with a reduced but essential amount of data from defined and unique data sources, direct access to colleagues working results and synchronizing work lead to an enormous saving in time and effort. Thus it is possible to operate more agile in the daily routines.


adaptable according to your demands

The system is based on linking data objects (data atoms) with each other. Expanding this data mesh can be data at anytime. A so called "big bang" isn't necessary. Start with a small department (set of pain points) and expand it step by step, according your available capacities. 


cross company and multiple domain

Modeling does not reflect your your current organizational structure or the production processes and is not limited to your own company. The possibility of integrating partner data and different domains  (compliance regulations) is pre-condition for covering legally obligations and using "open data".


perfect for "not planned" cross-department data analysis

Usually relational data models are designed for specific processes and ranges of queries. In these models it could be a real challenge to run queries which were not known in the moment of defining the data model. In a semantic model it is possible to define any queries that are necessary any time as a mesh does not care about any direction. No matter whether you want to analyse top down or bottom up.


basis for company wide knowledge management

Integrated modeling of physical parts and their functions is a pre-condition for MBSE (model based systems engineering) and the implementation of knowledge management methods.


semantic "blockchain"

Every data atom stays in the system from it's moment of creation. Deleting it is not possible, only deactivating is offered. Thus a sudden loss of data is prevented. Every node has its own history where the explicit documentation of changes and users can be found. The end result is a kind of "semantic blockchain" - a documentation of a product including its history of creating.