Skip to main content

AI Assistant Capabilities: Table Templates

SqlDBM Support
Updated

I can help you create, customize, and leverage table templates to standardize and accelerate your data modeling workflow. Here's what I can do:

Creating Custom Templates

From Scratch

I can author new table templates in YAML format based on your requirements. Tell me:

  • The modeling pattern you need (dimensional, Data Vault, one big table, audit log, etc.)
  • Column standards (audit fields, metadata, primary keys)
  • Inheritance behavior (how to treat source table columns)
  • Naming conventions (prefixes, suffixes, transformation rules)

I'll generate the complete YAML definition, handle the syntax correctly, and validate it works with your project's rules.

By Learning from Your Model

I can analyze your existing tables to discover patterns:

  • Common column sets across table families
  • Naming conventions you're already using
  • Data type standards and constraints
  • Audit trail patterns

Then I propose templates that codify those patterns for reuse.

From Your Description

Describe what you're trying to standardize in plain language:

  • "I need every fact table to have batch tracking columns"
  • "Dimensions should always have effective dating"
  • "Audit tables need to capture who/when/what changed"

I'll translate your requirements into a working template definition.
 

Modifying Existing Templates

Read and Explain

I can examine your current templates and explain:

  • What structure they generate
  • When to use each one
  • How inheritance and relationships work
  • What the YAML properties control

Update and Enhance

I can modify templates to:

  • Add new default columns (audit fields, metadata, lineage tracking)
  • Change data types or nullability rules
  • Adjust column positioning (top, bottom, after inherited columns)
  • Modify naming patterns with template variables
  • Change inheritance modes (PK vs non-PK vs none)
  • Update relationship generation behavior

Fix Issues

If a template isn't working as expected:

  • I'll identify syntax errors or invalid field values
  • Correct enum values (relationship types, positions, inheritance modes)
  • Fix variable usage (${parentPhysicalName}, etc.)
  • Resolve conflicts between inherited and default columns

Using Templates in Your Workflow

Guided Creation

When you ask me to create a table, I can:

Recommend which template fits your use case

  • Create tables from templates with proper source table references
  • Generate multiple related tables from a single template (batch fact table creation)
  • Apply templates to existing tables as a refactoring step

Strategic Application

I understand when templates are appropriate:

  • Use templates for: Repeating patterns across many tables (facts, dimensions, audit logs, bridge tables)
  • Skip templates for: One-off specialized structures, temporary tables, external stage definitions

Inheritance Intelligence

I can help you leverage source table inheritance:

  • Create child tables that reference parent keys as FKs
  • Build dimension tables from staging tables with attribute inheritance
  • Generate fact tables from dimensions with proper key relationships
  • Create view layers that inherit structure from base tables

Template Design Consultation

Pattern Recognition

I can identify opportunities for templates by:

  • Analyzing your model for repeated column patterns
  • Spotting inconsistencies that templates would prevent
  • Finding tables that share structural DNA
  • Recognizing modeling methodologies (Kimball, Data Vault, Anchor, etc.)

Best Practice Guidance

I'll advise on:

  • Inheritance modes — when to use pk vs non-pk vs none for identifiers
  • Column positioning — strategic use of first/last for readability and maintenance
  • Relationship generation — physical vs virtual FKs based on your constraints strategy
  • Variable usage — leveraging ${parentPhysicalName} and other variables for dynamic naming
  • Attribute inheritance — when to copy vs when to reference

Domain-Specific Templates

I can design templates tailored to:

  • Financial services — fact tables with currency/party/date FKs, regulatory audit columns
  • Healthcare — HIPAA audit trails, patient/provider dimensions, clinical event facts
  • Retail — product hierarchies, transaction facts, customer dimensions
  • SaaS — usage metrics, subscription facts, tenant dimensions
  • Any domain — I adapt to your business vocabulary and metadata requirements

Template Analysis & Optimization

Inventory and Documentation

I can:

  • List all templates in your project with their purposes
  • Compare default vs custom templates
  • Identify unused or redundant templates
  • Document what each template generates (structure preview)

Impact Analysis

Before template changes, I can:

  • Find which tables were created from a specific template
  • Assess how template modifications would affect future table creation
  • Identify where template column attachment/detachment would help

Quality Checks

I'll validate templates for:

  • Data type consistency with your existing dimensions
  • FK compatibility (ensuring template FKs match target PK types)
  • Naming convention alignment
  • Missing audit/governance columns based on your standards

Integration with Model Operations

Combined Workflows

I can chain template usage with other modeling actions:

  • Create table from template → add to diagram → apply layout
  • Generate multiple fact tables → establish relationships → set colors by subject area
  • Build dimension from source → create satellite → link to hub
  • Apply template → add descriptions → set governance field values

Relationship Automation

When templates generate relationships, I:

  • Verify FK column name matching (exact, prefixed, camelCase)
  • Ensure data type compatibility
  • Create physical or virtual relationships per template config
  • Add relationship display names automatically

Post-Creation Refinement

After creating from template, I can:

  • Remove duplicate columns caused by inheritance conflicts
  • Rename generated tables to better match grain
  • Add domain-specific columns the template doesn't cover
  • Attach column templates for cross-cutting concerns

Template Strategy Development

Starter Kit Creation

For new projects, I can establish:

  • Core template library (2-5 templates covering 80% of your tables)
  • Naming and structure conventions
  • Audit column standards
  • Relationship patterns

Migration Support

When standardizing an existing model:

  • Identify template candidates from existing table families
  • Create templates that match current patterns
  • Plan gradual adoption strategy
  • Maintain backward compatibility

Governance Integration

I connect templates to broader governance:

  • Ensure templates include columns for Model Governance fields
  • Align with dbt property patterns
  • Support lineage tracking columns (batch_id, source_system)
  • Embed compliance metadata (data classification, retention policies)

Technical Execution

What I Handle Automatically

  • YAML syntax — correct structure, proper indentation, valid field names
  • Enum values — relationship types, positions, inheritance modes, materializations
  • Variable substitution — proper use of ${parentPhysicalName} and other template variables
  • Error recovery — if template creation fails, I read the error, fix the issue, and retry silently

What I Need from You

  • Intent — what pattern you're trying to standardize
  • Domain context — business meaning helps me choose appropriate defaults
  • Exceptions — any tables or cases where the template shouldn't apply
  • Preferences — when multiple valid approaches exist, your choice guides me

Key Principles I Follow

  1. Templates are for patterns, not one-offs — I'll push back if you're templating something unique
  2. Inheritance is powerful but tricky — I'll warn about duplicate columns and type mismatches
  3. Names matter — template physical names should reflect grain and purpose
  4. Audit is non-negotiable — I'll advocate for lineage and timestamp columns in every template
  5. Documentation lives in descriptions — I'll remind you to add template descriptions explaining when to use them

Learning and Adaptation

I continuously learn your project's idioms:

  • Naming patterns (prefixes like fct_, dim_, stg_)
  • Data type conventions (varchar lengths, decimal precision)
  • Relationship styles (physical constraints vs virtual documentation)
  • Governance maturity (basic audit vs comprehensive lineage)

The more you work with me, the better my template suggestions align with your established patterns.

In summary: I'm your template architect and automation engineer. I don't just create YAML files—I help you think through standardization strategy, encode best practices, and build reusable patterns that accelerate your modeling work while maintaining consistency and quality.
 

Related articles