If the librarian doesn’t have a well-maintained catalog of books, it might take the librarian hours to find a particular book. Similarly, a data analyst, might take hours or it would be extremely difficult to find, obtain, and evaluate the necessary data if the data catalog is not available.
In addition, the data catalog has another important focus: providing a “Google search” to the enterprise data assets used in reports, dashboards, data warehouse tables, and more.
A semantic layer simplifies and translates technical data laos whatsapp number data into a language the businesses can understand. It works by converting the metadata from the data sources and the applications into a cross-organization semantic knowledge graph. The semantic layer sits between the data sources (source systems) and the analytics/AI tools, making it easier for people to access and analyze data without needing to understand the technical details. A semantic layer is like a translator that bridges the gap between business language and data language by bringing consistent and aligned business data definitions.
However, for the semantic layer to work well it requires robust metadata that is enterprise-wide. Metadata plays a crucial role in the formation of the semantic layer, but also in the monitoring of changes over time, which are being reflected immediately in all semantic layer-based applications.