Modernization, in many ways, is often synonymous with centralization. Creating a unified framework from which all enterprise systems derive ensures frictionless operations through a sense of standardization. Semantic layers are a key strategy in establishing this framework, capable of seamlessly connecting traditional BI, self-service analytics, and emerging AI/ML workloads.
In a new series brought to you by DBTA and Radiant Advisors, John O'Brien, principal advisor and CEO, Radiant Advisors, explored the crucial relationship between semantic layers and modern enterprise analytics, powering opportunities today and the AI capabilities of tomorrow.
The Radiant Ascent Webinars will explore modern enterprise data and analytics architecture, featuring monthly deep dives into emerging technologies and best practices. In each episode, O’Brien will guide attendees through a new technical summit, unpacking complex architectural challenges and revealing proven strategies.
In this episode, Unifying Enterprise Analytics: The Critical Role of Modern Semantic Layers, O’Brien emphasized that “data architectures enable something. You don’t build an architecture for the sake of architecture…they all had a purpose.”
These purposes—whether it’s short-term or long-term—align architectures with business goals. O’Brien highlighted three key frameworks—or “purposes”—as observed by Radiant where a semantic layer plays a role: enterprise analytics capabilities; user journey for gap analysis; and logical modern data architecture.
Examining the first of these frameworks, O’Brien explained that the semantic layer “unifies analytics in the end user’s journey. If somebody is coming in and wants to find the data products that are available; find data sources they can work with; find metrics and reports; understand where that data came from; collaborate, work on that—that has been our bundle inside of what we now call the unified semantic layer.”
Using a conceptual architecture, the semantic layer represents “the knowledge that needs to go in here [the architecture] from the data that’s underlying it, and that is the real key. As a business user coming in, we want them to come to one place.”
Drilling into the role of the semantic layer as it relates to architecture and analytics, O’Brien identified five critical requirements:
- Open architecture principle
- Agility for faster bimodal development process
- Lineage, usage, and collaboration
- Modern OLAP with intelligent aggregate caching
- Comprehensive API registry
Each of these requirements plays a crucial role in creating a unified semantic layer, according to O’Brien. Notably, O’Brien emphasized the idea of an open semantic layer, capable of independently connecting to many diverse databases and consumer tools. By avoiding closed, tool-specific semantic layer products that create data silos between BI and AI, enterprises benefit from a consistent layer with singular definitions, cultivating a truly unified framework.
This is only a snippet of our new webinar series with O’Brien and Radiant Advisors. To view the full webinar, featuring in-depth examinations, use case examples, a Q&A, and more, you can view an archived version of the webinar here.