How Mosaic liberates your data

In the world of data analytics, we often find ourselves building dashboards and reports that, while useful, can quickly become siloed and inconsistent. Every team, every analyst, and every tool might be defining the same key metrics differently, leading to confusion, wasted effort, and mistrust in the data.

What if there was a better way? What if we could define our data's meaning just once, in a central place, and have every visualization tool, every report, and every user benefit from that single source of truth? This is the core promise of a semantic layer, and it's what our latest demo is all about.

The Added Value of a Semantic Layer

Think of a semantic layer as a centralized translation hub for your data. Instead of raw data tables, it presents a business-friendly view of your data, with clear definitions for things like "Total Sales," "Customer," or "Active Users."

Here's why this is a game-changer:

• Single Source of Truth: By defining metrics (and business logic in general) centrally, we eliminate conflicting calculations. This ensures everyone, from marketing to the C-suite, is looking at consistent numbers, which builds trust and aligns the entire organization.
• Centralized Governance: If a business rule changes—for example, how we calculate a new metric—we only need to update it in one place: the semantic layer. This change then automatically propagates to every report and dashboard that uses it.
• Enhanced Reusability & Vendor Independence: This is perhaps the most powerful benefit. Once your data model is defined in the semantic layer, any visualization tool, be it Power BI, Tableau, or something else, can connect to it and leverage its structure. This fundamentally breaks the cycle of vendor lock-in, allowing us to choose the best tool for the job without sacrificing data consistency.
  
  
  

Our Demo: Strategy (Mosaic), PowerBI, and Hypercards

To prove these concepts aren't just theoretical, we built a demo with three key components:

• The Foundation (Strategy's Mosaic): We started by creating a semantic graph in Strategy. Even though this is a very simple example, you can look at it like a data model that understands the relationships between our key business entities.
  
  
  
  
• The Visualization (Power BI): Next, we used Power BI to build a dashboard. The crucial part? We didn't connect Power BI to the raw data. We connected it directly to the Strategy semantic graph. This allowed the Power BI report to instantly inherit all the governed metrics and
  business logic we had already defined in Strategy!
  
  
  
  
• The Intelligent Overlay (Strategy Hypercard): This is where the magic happens. On top of the Power BI dashboard, we built a Hypercard in Strategy. This Hypercard is designed to find matches and provide context to the data displayed in the Power BI report or actually any other webpage or application. It’s an intelligent layer that complements the standard dashboard, providing deeper insights without leaving the user's workflow.
  
  
  
  
  

Unleashing the Power of AI: The AutoBot

Typically, Strategy's AI offering is called 'Auto' followed by the purpose of the AI. For example: Auto Dashboard allowing you to create a whole dashboard automatically by just asking, Auto Narratives which allows you to create summaries, Auto SQL enabling you to write or explain SQL queries, and finally the Auto feature we used, Auto Bot!

Integrated directly into the Hypercard, the AutoBot adds a conversational layer to the data.

How it works: The AutoBot can answer questions about the data in human language. You can ask it, "Which products had the highest sales last quarter?" and it will provide an accurate, data-backed answer based on the underlying semantic graph.

Why would this matter? This moves us beyond static dashboards. It empowers non-technical users to get instant insights without having to navigate complex reports or charts. It truly democratizes access to information and shows the immense possibilities when a strong semantic foundation is combined with the power of conversational AI.

Conclusion: Beyond a Simple Dashboard

Our demo is more than just a cool project; it's a blueprint for a modern data stack. It proves that a semantic layer is no longer a "nice-to-have" but a crucial component for data governance, reusability, and vendor independence. The combination of a strong semantic foundation with intelligent tools like Hypercards and AutoBots opens up a world of possibilities for how we interact with, understand, and leverage our data.

Ready to unlock the potential of your data? The journey begins with a single, well-defined semantic layer.