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Semantic Layer Optimization

The semantic layer is a crucial component of Data Neuron that bridges the gap between natural language queries and your database schema. Optimizing this layer can significantly improve the accuracy and efficiency of your queries.

Importance of Semantic Layer Optimization​

A well-optimized semantic layer:

  • Improves query accuracy
  • Enhances natural language understanding
  • Reduces ambiguity in entity recognition
  • Speeds up query processing

Best Practices​

  1. Use Descriptive Names: Choose clear, descriptive names for tables and columns in your semantic layer.

  2. Add Aliases: Provide common aliases or alternative names for entities to improve query interpretation.

  3. Include Business Definitions: Add detailed business definitions for tables and columns to enhance context.

  4. Define Relationships: Clearly specify relationships between tables to enable more complex queries.

  5. Optimize for Common Queries: Tailor your semantic layer to support frequently asked questions.

Example Optimization​

Here's an example of an optimized semantic layer definition:

tables:
  - name: sales
    description: "Record of all sales transactions"
    aliases: ["transactions", "orders"]
    columns:
      - name: sale_date
        description: "Date of the sale"
        aliases: ["transaction_date", "order_date"]
      - name: customer_id
        description: "Unique identifier for the customer"
        relationships:
          - table: customers
            column: id

definitions:
  - term: "revenue"
    definition: "The total amount of money earned from sales"
    calculation: "SUM(sales.amount)"

Optimization Process​

  1. Analyze Current Queries: Review common queries to identify frequently used terms and concepts.

  2. Map Business Terminology: Align your semantic layer with the business terminology used in your organization.

  3. Iterate and Test: Continuously refine your semantic layer based on query performance and user feedback.

  4. Use Data Neuron CLI: Utilize the Data Neuron CLI to manage and update your semantic layer:

    dnn --update-context your_context_name

  5. Version Control: Keep your semantic layer definitions in version control to track changes and collaborate with team members.

Next Steps​