Data Analytics - Reporting Semantics in Legacy Data
All data and texts for all of a company's products and services are often historically distributed across different information systems. Product information on the same product must therefore be searched for in different inventory systems. In addition, effort is required to interpret the differently named data in these systems. As a result, the company increasingly loses its business basis and ability to innovate due to the limited availability of this data and text.
The Problem of Fragmentation and Data Storage
A company's inventory system landscape is usually fragmented. Each subsystem has historically been subject to different IT conditions with corresponding consequences for the data and texts to be managed. To access information on the same product, different search masks have to be used in different systems.
The same characteristics of all products of a company often have different, e.g. synonymous, designations and different perceptions of value ranges. Research in these different inventory systems is therefore often limited to a small circle of specialists.
Added to this are the limited possibilities of the conventional relational databases of inventory systems. The entire reality of the product properties had to be transferred to tables and columns and thus greatly simplified semantically.
Solution for the Integration and Consolidation of Inventory Data
Graph databases are unlimited in describing all the properties of a product. They are therefore suitable for mapping the entire, even multilingual, terminology, for describing all of a company's products and services as an ontology.
The ontology then summarizes all data and texts semantically in the form of a cross-system knowledge graph. Integration takes place via technical interfaces or by transferring data in the graph database as a migration.
Reporting of all Inventory Data as a Basis for Decision-Making
An analysis of all inventory data creates a basis for decisions on the current status of all feature designations and the data and texts assigned to them for all products.
On this basis, a decision can then be made on the continuous integration of the data and texts of the remaining inventory system or, alternatively, on a migration to the graph database to replace the inventory system and the revision and semantic expansion of the data and texts.
The basis for a comprehensive semantic product information system as a digital twin of all of a company's products and services is ultimately a consolidated and revised product database.