Documentation Index
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Maps values from a source field to new values using a lookup dictionary - similar to VLOOKUP in spreadsheets. Supports inline key-value pairs, entity-based dictionaries, and fuzzy matching.
Configuration
| Setting | Description |
|---|
| Source Field | The field to use as the lookup key |
| Dictionary Source | Inline (key-value pairs defined in the node) or Entity (from a connected integration) |
| Result Field Name | Name for the output field (default: lookup_result) |
| Default Value | Value to use when no match is found |
| Match Mode | How to match keys (see below) |
| Case Sensitive | Whether matching is case-sensitive (default: off) |
| Virtual Object Name | Namespace prefix for output fields (default: dictionary_lookup) |
Inline Dictionary
| Setting | Description |
|---|
| Entries | List of key-value pairs |
Entity Dictionary
| Setting | Description |
|---|
| Dictionary Key Field | Field in the reference entity to match against |
| Dictionary Value Field(s) | Field(s) to return from matching rows |
| Dictionary Filter Field | Optional field for filtering/grouping lookups |
Match Modes
| Mode | Description |
|---|
| Exact | Key must match exactly (default) |
| Fuzzy | Uses similarity scoring with configurable threshold (0-100) |
| Fuzzy Top N | Returns top N fuzzy candidates |
| Regex | Dictionary keys are regex patterns - first match wins |
| Substring | Longest matching substring wins |
| Collect All | Joins all matching values from a filtered group |
Fuzzy Matching Options
| Setting | Description |
|---|
| Fuzzy Threshold | Minimum similarity score (0-100, default: 70) |
| Fuzzy Scorer | Scoring algorithm: WRatio (default) or Token Set Ratio |
| Noise Words | Words to strip before matching |
| Normalize Umlauts | Normalize German umlauts (ä→ae, etc.) |
| Substring Boost | Boost substring matches to score 95 |
How It Works
Select the source field
Choose which field contains the values to look up.
Define the dictionary
Use inline key-value pairs for simple mappings, or reference an entity for larger dictionaries.
Choose a match mode
Use Exact for clean data, Fuzzy for messy data, or Regex for pattern-based mapping.
Output
A new field containing the matched dictionary value. For entity mode with multiple value fields, multiple columns are returned (like a multi-column VLOOKUP).
Examples
Inline: Map country codes to names
- Source Field: Country Code
- Dictionary Source: Inline
- Entries:
US → United States, GB → United Kingdom, DE → Germany
- Default: “Unknown”
Entity: Fuzzy company name matching
- Source Field: Company Name
- Dictionary Source: Entity (reference list of canonical company names)
- Match Mode: Fuzzy
- Threshold: 80
- Noise Words: “Inc, LLC, Ltd, Corp”
Best Practices
- Use Inline for small, static dictionaries (< 50 entries)
- Use Entity for large or frequently updated dictionaries
- Start with a higher fuzzy threshold (80+) and lower gradually if needed
- Use Noise Words to strip common suffixes before fuzzy matching (e.g., company suffixes)
- Use Collect All mode when you need to aggregate all matching values
- Reference Lookup - looks up matching rows and formats as text
- Transform - use CASE expressions for simple value mapping without a dictionary
- Find Duplicates - fuzzy matching across records rather than against a dictionary
