Why Read This?
What’s the semantic layer? How can your analytics team leverage it? How does it bridge AI & BI?
Read this bundle of Semantic Layer whitepapers to learn the key value propositions to implement a semantic layer and best practices for analytics success with one.
Companies need quicker and better insights and have hence deployed numerous data and analytics solutions across diverse data platforms – cloud and on-prem. This distributed set-up has created challenges in data quality, literacy, adoption and ultimately business performance.
The semantic layer can reduce complexity/costs, improve security, and streamline reporting for the business users in today’s complex data environments.
The semantic layer links the analytics consumption platform with the data platforms using the facts (data values), dimensions (data attributes) and hierarchies (i.e., taxonomies) in the Data Warehouse or any other cloud data platforms.
By abstracting the physical form and location of data, the semantic layer platform makes data stored in the canonical data platforms accessible with the one consistent and secure interface for the business users.
