Semantic Layer

What Is a Semantic Layer?

A Semantic Layer is a business-friendly abstraction that sits between your raw data and your reports. It translates complex database tables into understandable business concepts—metrics like “Revenue” and dimensions like “Product Category”—with consistent definitions that apply everywhere.

In Go Fig, the Semantic Layer ensures that:

• “Revenue” means the same thing in every report
• Calculations are defined once and applied consistently
• Business users don’t need to understand database schemas
• Changes to definitions automatically update all reports

Why Does the Semantic Layer Matter?

The Problem Without It

Without a semantic layer, organizations suffer from “spreadsheet chaos”:

• Sales calculates revenue one way, Finance another
• The CEO sees different numbers in different reports
• Every analyst recreates the same calculations
• Errors propagate when formulas are copy-pasted
• Nobody trusts the numbers in meetings

The Solution

The Semantic Layer establishes a single source of truth for business logic:

• One definition of “Revenue” used everywhere
• Consistent calculations across Excel, dashboards, and AI
• Changes made once, reflected everywhere
• Business users trust the numbers

Semantic Layer Components

Metrics (Measures)

Quantitative values you want to analyze:

• Revenue
• Gross Margin
• Customer Count
• Average Order Value
• Days Sales Outstanding

Each metric has a precise definition:

Revenue = SUM(order_amount) WHERE order_status = 'completed'

Dimensions

Categories for slicing and filtering metrics:

• Time (Year, Quarter, Month, Week, Day)
• Geography (Country, Region, State, City)
• Product (Category, Subcategory, SKU)
• Customer (Segment, Industry, Size)
• Organization (Business Unit, Department, Cost Center)

Relationships

How dimensions connect to metrics:

• Revenue by Product Category
• Customer Count by Region
• Margin by Time Period

Business Logic

Rules and calculations that reflect your business:

• Fiscal calendar definitions
• Currency conversion rates
• Allocation methodologies
• Recognition rules

How Go Fig Builds Your Semantic Layer

1. Connect Data Sources Go Fig pulls raw data from your ERPs, databases, and spreadsheets.

2. Map to Business Concepts Our team works with you to define metrics and dimensions that match how your business thinks about data.

3. Apply Business Logic We configure calculations, hierarchies, and relationships based on your requirements.

4. Validate Compare semantic layer outputs to existing reports to ensure accuracy.

5. Deploy The semantic layer powers all Go Fig features—Excel sync, dashboards, Celeste, and workflows.

Semantic Layer in Action

In Excel

When you sync data to Excel, Go Fig delivers metrics calculated using semantic layer definitions. Your formulas reference consistent, pre-calculated values.

In Dashboards

Dashboard visualizations display semantic layer metrics. Click on “Revenue” and you see the same number as in your Excel reports.

With Celeste

When you ask Celeste “What was revenue last quarter?”, she queries the semantic layer and returns a number calculated using your defined logic.

In Workflows

Automated workflows reference semantic layer metrics for validation, alerts, and reporting.

Semantic Layer vs. Raw Data Access

Aspect	Raw Data	Semantic Layer
User skill required	SQL knowledge	Business concepts
Consistency	Varies by query	Guaranteed
Calculation errors	Common	Prevented
Time to answer	Minutes to hours	Seconds
Governance	Difficult	Built-in

Managing the Semantic Layer

Version Control

All changes to the semantic layer are versioned. You can see what changed, when, and why.

Testing

Changes can be validated before deployment to ensure they don’t break existing reports.

Documentation

Every metric and dimension includes descriptions, formulas, and business context.

Access Control

Define who can modify the semantic layer (typically Finance leadership) vs. who can consume it (everyone).

Getting Started

Go Fig’s white-glove implementation includes building your semantic layer. Our team:

1. Interviews stakeholders to understand metric definitions
2. Documents current calculations and identifies inconsistencies
3. Proposes a unified semantic model
4. Builds and validates the layer
5. Trains your team on governance

Most implementations complete the initial semantic layer within 2-3 weeks of starting.