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Adds a skill for authoring Tableau Next semantic models (SDMs) on Data 360: build from scratch, add data objects, define joins, enrich with calculated fields and metrics, and make models AI-ready. Smoke-tested against a live Data 360 org: SDM discovery, AI-readiness flip, dimension creation, metric creation, and description backfill all exercised end-to-end.
1.6 KiB
1.6 KiB
Calculated Field Patterns
Aggregation types + common expression patterns for creating _clc measurements and dimensions. Companion to the create-a-calc-field workflow in SKILL.md.
Aggregation Types
When creating measurements, choose the correct aggregation type based on how the field should behave in visualizations:
| Aggregation | Use When | Example |
|---|---|---|
Sum |
Additive values (revenue, count) | SUM([Table].[Amount]) |
Avg |
Average needed (rates, percentages when raw values available) | AVG([Table].[Close_Days]) |
UserAgg |
Expression already includes aggregation | SUM([Table].[Won]) / SUM([Table].[Total]) |
Min |
Minimum value | MIN([Table].[Close_Date]) |
Max |
Maximum value | MAX([Table].[Amount]) |
Count |
Row count | COUNT([Table].[Opportunity_Id]) |
Critical: Don't guess aggregation types. If uncertain, inspect the SDM first to see how similar fields are configured, or use UserAgg when your expression already includes aggregation functions.
Common Expression Patterns
Time calculations:
DATEDIFF('day', [Table].[Created_Date], [Table].[Close_Date])
Conditional aggregation:
SUM(IF [Table].[Stage] = 'Closed Won' THEN [Table].[Amount] ELSE 0 END)
String manipulation:
UPPER([Table].[Account_Name])
LEFT([Table].[Opportunity_Name], 10)
Null handling:
IFNULL([Table].[Amount], 0)
See tableau-functions.md for complete function reference and patterns.md for production-derived ratio / LOD / dimension patterns.