The term \u201eSemantic Data Management\u201c is particularly relevant in the fields of Big Data and Smart Data, Artificial Intelligence, and Digital Transformation. It describes methods and technologies that enable not only the storage of large amounts of data, but also the structuring and linking of data in such a way that computers can understand their meaning.<\/p>\n
Through semantic data management, information is enriched with additional clues, known as metadata. This allows relationships between different datasets to be recognised and utilised. This makes it easier for companies to extract knowledge from their data and make better decisions.<\/p>\n
For example: In a company, customer data, product information, and order histories are often stored separately. Semantic data management can be used to link this information together. When a customer places a particular order, the system can automatically recommend suitable additional products because it understands the relationships between different products and customers.<\/p>\n
Overall, semantic data management makes working with data more efficient, saves time on research, and opens up new possibilities for automating and optimising business processes.<\/p>","protected":false},"excerpt":{"rendered":"