Microsoft Dynamics 365 Customer Experience Analyst : Configure Dataverse search
Dataverse Search is a powerful, relevance-based search capability in Microsoft Dataverse that allows users to quickly find information across multiple tables and records. Unlike traditional quick find or advanced find, it uses a full-text search engine with natural language processing, enabling more accurate results through ranking, tokenization, and stemming. Users can search across related data, leverage filters and facets, and even discover insights that might not be immediately visible through standard queries. It improves productivity by providing a single, centralized search experience in model-driven apps, helping users retrieve the right records faster and make better business decisions.
Configuring Dataverse Search
Dataverse Search is enabled at the environment level and then fine-tuned at the table level. It uses a full-text search index in Dataverse to deliver fast, relevance-ranked results. Here’s how you configure it:
1. Enable Dataverse Search in the Environment
- Sign in to the Power Platform Admin Center.
- Navigate to Environments → select the environment you want to configure.
- Under Settings → choose Features.
- Locate Dataverse Search and toggle it ON.
- This enables indexing of data across tables.
- The search index will take time to build depending on the number of records.
Tip: Once enabled, Dataverse Search replaces the legacy “Relevance Search” in model-driven apps.
2. Configure Tables for Search
Not all tables are automatically included. You must configure which ones are searchable:
1. Go to Power Apps Maker Portal → select your environment.
2. Choose Solutions → open the solution that contains your tables.
3. For each table:
- Go to Settings → Search.
- Enable "Make this table searchable".
- Define searchable columns (fields) like Name, Email, Subject, Case Number, etc.
- Set facets and filters (optional) → allows users to refine search results.
Tip: Be selective — adding too many columns can slow down search indexing.
3. Configure Facets & Filters
Facets allow users to filter search results more effectively. For example:
- In Cases: filter by Status (Active, Resolved).
- In Contacts: filter by City or Account.
Configuration steps:
- From the table’s Search settings, choose which fields should be facets.
Example: `City`, `CreatedOn`, `Owner`, `Status`.
4. Security & Permissions
Dataverse Search respects Dataverse security roles.
- Users only see results for records they have access to.
- No special configuration is required — it inherits from security model.
5. Test the Search
Once indexed, test in your model-driven app:
- Use the search box in the app header.
- Enter keywords and see results across multiple tables.
- Verify that ranking, filters, and facets work as expected.
6. Best Practices
- Limit searchable fields → only include meaningful columns.
- Enable for high-value tables (like Contacts, Accounts, Cases).
- Monitor indexing performance in the Power Platform Admin Center.
- Keep data clean → consistent formatting improves search quality.
Example:
If you enable Dataverse Search for Cases, Contacts, and Accounts:
- A user searching for "John Doe" will see related Contacts, linked Accounts, and any Cases involving John Doe.
- Facets like Status = Active or Created in Last 30 Days help refine results.
This makes Dataverse Search far more powerful and user-friendly than Advanced Find, especially for quick, relevance-based lookups.
Summary:
Dataverse Search is a powerful, relevance-based search capability in Microsoft Dataverse that enables users to quickly find and explore data across multiple tables and records. Unlike Advanced Find, it uses a full-text search engine with natural language processing to deliver faster and more accurate results. It supports cross-table searching, ranking, and filtering with facets, making it easier to discover related records. Dataverse Search respects security roles, ensuring users only see data they’re authorized to access, and provides a centralized, user-friendly search experience that improves productivity in model-driven apps.
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