dataverse

name	dataverse
description	Dataverse Schema and Data Modeling. Use when: designing tables, columns, relationships, alternate keys, security roles, cascade behaviors, elastic tables, virtual tables, Dataverse search, query patterns (OData/FetchXML), naming conventions.

Skill: Dataverse Schema & Data Modeling

When to Use

Trigger when designing tables, columns, relationships, security roles, views, or querying Dataverse via OData/FetchXML.

---

Table Type Selection

Factor	Standard Table	Elastic Table	Virtual Table
Data volume	< 10M rows	10M+ rows, high write throughput	External data (no copy)
Transactions	Full ACID (multi-record)	Per-record only	None
Security	Full row/column	Organization-owned only	Organization-owned only
BPF support	Yes	No	No
Charts/dashboards	Yes	No	No
Calculated/rollup	Yes	No	No
TTL auto-expiry	No	Yes	N/A
Offline support	Yes	No	No
Best for	Business data, CRUD apps	IoT, logs, telemetry, high-volume ingestion	Read-only external data (SQL, SharePoint, Fabric)

---

⚠️ REQUIRED: Load Sub-Files Before Implementation

SKILL.md is a summary only — it is NOT sufficient for implementation.

The detailed content (complete payloads, XML templates, working examples, edge-case handling) lives in sub-files in the same directory as this SKILL.md. Before writing any code, you MUST use read_file on the sub-files relevant to your task:

• Table Design — Table design principles, column type guide, auto-number columns, alternate keys
• Relationships — N:1, 1:N, N:N, manual intersect tables, cascade behaviors
• Query Patterns — OData queries, FetchXML, lookup handling in Code Apps, schema discovery via metadata API
• Naming Conventions — Publisher prefix, table/column/relationship naming standards
• Elastic & Virtual Tables — Elastic tables (Cosmos DB), virtual tables, Dataverse search, long-term retention

---

Anti-Patterns

• Text columns used as primary identifiers without alternate keys
• Cascade delete without documenting intended behavior
• Org-owned tables where row-level security is needed
• Rollup columns on tables with millions of rows
• Storing JSON blobs in text columns to avoid proper schema
• Duplicate choice definitions across tables (use global option sets)
• N:N relationship used when the intersect needs attributes
• Missing indexes on frequently-filtered lookup columns
• Over-permissive security roles ("just give them System Admin")

---

Related Skills

• dataverse-web-api — CRUD operations and metadata management via API
• security — Security roles, column security, row-level access
• plugins — Server-side logic operating on Dataverse schema
• code-apps — Client-side Dataverse queries from React
• model-driven-apps — Forms and views built on Dataverse tables