Core Workflow

Explore Datasets

The Dataset Explorer is where you verify and refine your survey data before analysis. It has three main views: Variables, Question Groups, and Raw Data.

Core Workflow

Variables view

A table of every variable in the dataset showing:

  • Variable name (original from the file)
  • Label (human-readable description)
  • Type badge — colour-coded: C (Categorical), B (Binary), S (Scale/Numeric), T (Text), W (Weight)
  • Group membership

Tip

Use this view to scan the full variable list, search for specific fields, and spot type issues.

Core Workflow

Question Groups view

Variables grouped by their parent question. Useful for:

  • Understanding array structures (e.g. a grid question with multiple items)
  • Verifying that related variables are grouped correctly
  • Identifying groups that need manual adjustment

Core Workflow

Raw Data view

A paginated record-level grid for spot-checking actual values.

  • Filter columns to focus on specific variables
  • Click a variable in the Variables tab to scroll to it in Raw Data
  • Use this to verify suspicious categories, check missing-value patterns, or confirm that a weight variable looks reasonable

Core Workflow

Editing metadata

Variable names, labels, and value labels are editable directly in the explorer. Changes propagate to:

  • Table headers and row stubs
  • AI agent context (the agent sees updated labels)
  • Exported project files

Clean metadata drives better AI

Good AI output starts with clean metadata. If labels are unclear or grouping is wrong, fix it here first. The agent reads the same metadata you see in the explorer.

Core Workflow

Group-synced editing

For categorical array questions (grids), editing a value label in one member variable updates it across all members of the group. This prevents inconsistency in array-structured data.