How Mosaic Is Redefining the Semantic Layer for the Modern Data Stack

The Need for Data Clarity

Data clarity is no longer optional—it’s a strategic requirement. 
As companies adopt cloud-first architectures, multi-cloud environments, and increasingly sophisticated business analytics tools, two challenges remain:  

• How do you manage and scale business logic across disparate data sources and tools without losing critical insights? 

• How do you deliver those data insights across roles, teams, and locations? 

This is where Mosaic, our next-generation semantic layer, comes in—not just as a feature but as a foundational shift in how enterprises model, access, and scale data intelligence. 

Challenges in Modern Data Management Solutions

Historically, semantic layers have resided within BI tools (such as Power BI or Tableau), while much of the business logic has been embedded directly within data warehouses. While convenient at first, this tight coupling introduces significant challenges. 

• When business logic is modeled within a data warehouse, any change in the backend infrastructure requires a restructuring of the entire layer. 

• Data restructuring isn’t just a technical headache—it’s a business liability. Your developers turn into silos, data processes become slow, and analytics suffer. 

• If you need to switch to a different data warehouse, you must rewrite your logic, migrate your data, and rework every dashboard, report, and downstream application.  

• Security rules and governance models must often be rebuilt from scratch—introducing unnecessary risk, delays, and inconsistency. 

This lack of portability causes infrastructure lock-in—where enterprises can’t modernize their data management systems, limiting innovation. Mosaic was built to solve this problem. 

Decoupling Logic from Storage with Mosaic

Mosaic introduces a Universal Intelligence Layer—a portable, scalable solution that cleanly separates business logic from underlying data storage and consumption tools. 

Business logic and security definitions are modeled independently, allowing organizations to switch data warehouses or migrate between clouds without disrupting downstream analytics or data products.

Simply put, Mosaic allows you to point your semantic layer at a new cloud platform or a different data source—without rewriting your metrics, remapping security roles, or retraining your users.   

Whether you're running Fabric on Azure, Redshift on AWS, or BigQuery on GCP—Mosaic’s Universal Intelligence Layer remains consistent and portable. 

Tool-Agnostic Access for Every User

One of Mosaic’s most significant advantages is its tool-agnostic access model. With Mosaic, the same semantic layer serves Power BI, Tableau, Excel, Google Sheets, SQL tools, and even REST APIs—without duplication or inconsistencies in logic.

This enables every user, from analysts to executives, to get consistent, trustworthy data through their preferred tools—all powered by Mosaic. 

This feature becomes especially powerful when metrics require complex definitions.  

For example, inventory can be summed across stores but requires special calculations across time periods. 

Since the definitions and rules are embedded in the semantic layer, every query—regardless of its source—delivers accurate, governed results.

Modern, AI-Powered Modeling with Accelerated Delivery

Compared to legacy modeling platforms, Mosaic’s AI-powered data modeling is significantly faster and more intuitive. With Mosaic, you can build data models 10x faster and enable quicker development of data products, departmental dashboards, and AI initiatives.

Moreover, Mosaic integrates with your existing investments, providing an innovative BI solution without requiring a full rip-and-replace strategy.  

• Current customers can continue using Schema technology while adding Mosaic capabilities. 

• New customers can layer Mosaic over existing models to immediately gain cross-platform benefits without rebuilding the entire infrastructure.

Ready for AI and Virtualization

The rise of AI and the increasing complexity of enterprise data landscapes have made the need for structured, high-quality data more urgent than ever. Mosaic is designed to meet that need head-on. 

By centralizing business definitions and data rules in one semantic layer, Mosaic ensures AI systems work with accurate, consistent information rather than raw, unverified data. 

In short, Mosaic bridges the gap between the chaos of raw data and the clarity needed for intelligent decision-making. 

It’s not just about faster reports; it’s about powering smarter decisions at scale.