The Value of Using a Semantic Layer
A semantic layer fills a void left in many analytic architectures. It is a centralized place to define business logic, ensure reporting is consistent, accelerate insights and make data more consumable. A semantic model is a key component in a semantic layer platform. The value of semantic models is clear. Nearly twice as many organizations using semantic models (62% vs. 33% overall) report that their analytics capabilities are completely adequate, while twice as many (51% vs. 25% overall) report that their data governance capabilities are completely adequate. In fact, organizations that have successfully implemented a semantic model are more than twice as likely to report satisfaction with analytics (77%) compared with a 33% overall satisfaction rate. But a semantic model should go beyond data. To be truly useful, a semantic model must include calculated pieces of information that are critical to understanding an organization’s operations.