Enhancing Q&A with Synonyms and Phrases

Power BI Q&A allows users to ask questions about their data in natural language and get instant chart or table answers. Out of the box, Q&A interprets table names, column names, and relationships to generate reasonable results. But "reasonable" is not "accurate"—without configuration, Q&A frequently misinterprets business terminology, selects wrong measures, and returns confusing visualizations. This guide covers how to configure synonyms, phrasings, and linguistic schema to make Q&A genuinely useful for business users.

How Q&A Processes Questions

When a user types "What were sales last month?", Q&A follows a multi-step process:

1. Tokenization: Break the question into meaningful tokens (what, were, sales, last, month)
2. Entity Recognition: Map tokens to model objects ("sales" → Sales Amount measure, "last month" → date filter)
3. Intent Detection: Determine the question type (aggregation, filter, comparison, trend)
4. Query Generation: Build a DAX query against the semantic model
5. Visualization Selection: Choose the best visual type for the result (card for single value, bar chart for comparison, line chart for trend)

Each step can fail if Q&A cannot map user language to model objects. Synonyms and phrasings fill the gaps between how users think about data and how the model is structured.

Configuring Synonyms

Synonyms tell Q&A that multiple words mean the same thing. Without synonyms, Q&A only recognizes exact column and table names:

Column Synonyms: In Power BI Desktop, select a table in model view, open the Properties pane, and expand Q&A setup. For each column, add synonyms that users might naturally use:

| Column Name | Synonyms to Add | |---|---| | SalesAmount | Revenue, Sales, Bookings, Income | | CustomerName | Client, Account, Buyer, Company | | ProductCategory | Category, Product Group, Product Line | | OrderDate | Date, Transaction Date, Purchase Date | | EmployeeCount | Headcount, Staff, FTE, Team Size |

Table Synonyms: Add alternative names for tables. If your table is named DimCustomer, add synonyms: Customers, Clients, Accounts. Users never think in terms of "Dim" prefixes.

Measure Synonyms: Critical for calculated measures. If you have a measure called "YoY Growth %", add synonyms: "year over year growth", "annual growth", "growth rate", "growth percentage".

Pro Tip: Review the Q&A usage analytics to see what terms users are actually typing. Failed queries reveal missing synonyms.

Configuring Phrasings

Phrasings define how entities relate to each other in natural language. They tell Q&A the semantic relationships between tables so it can interpret complex questions:

Name Phrasings: Define what a column "is" for an entity. "Customer Name is the name of Customers" allows Q&A to answer "Who are the customers?" or "Which customer had the most sales?"

Attribute Phrasings: Define descriptive properties. "Product Color is an attribute of Products" enables "Show me red products" or "What color are the top-selling products?"

Relationship Phrasings: Define how tables relate in business terms. "Customers buy Products" enables "What products did Contoso buy?" or "Which customers bought laptops?"

Preposition Phrasings: Define location or time relationships. "Sales happen in Regions" enables "What were sales in the West?" or "Show me top regions for sales."

Verb Phrasings: Define actions between entities. "Employees manage Departments" enables "Which department does John manage?" or "How many employees manage each department?"

Linguistic Schema

For advanced Q&A configuration, export and edit the linguistic schema YAML file:

Exporting: In Power BI Desktop, go to File > Options and settings > Options > Q&A > Edit linguistic schema. This opens the YAML editor where you can define synonyms, phrasings, and relationships in bulk.

Bulk Synonym Management: The YAML format allows adding dozens of synonyms efficiently rather than clicking through the GUI for each column. This is essential for models with hundreds of columns.

Custom Phrasings: YAML supports complex phrasing patterns that the GUI does not expose, including conditional phrasings and multi-hop relationship definitions.

Featured Questions

Featured questions appear as suggestions when users open Q&A, guiding them toward high-value insights:

Curation Strategy: Select 5-8 featured questions that demonstrate Q&A's capabilities and answer common business questions. Mix question types: "What were total sales this quarter?" (aggregation), "Which region grew fastest?" (comparison), "Show me sales trend over time" (trend analysis).

Maintenance: Update featured questions quarterly to reflect current business priorities. Remove questions that are no longer relevant and add new ones aligned with strategic initiatives.

Q&A Best Practices

Model Design for Q&A: Use business-friendly names for everything. Rename DimDate to Dates, FactSales to Sales, SalesAmountUSD to Revenue. Hide technical columns (surrogate keys, ETL timestamps) that confuse Q&A. Create explicit measures for every common calculation.

Testing with Real Users: After configuring synonyms and phrasings, invite 5-10 non-technical users to try Q&A. Watch what they type, note failures, and add missing synonyms iteratively. Three rounds of user testing typically resolves 90% of Q&A accuracy issues.

Q&A vs Copilot: Q&A is available to all Power BI users (Pro and above). Copilot requires Premium/PPU licensing but provides more sophisticated natural language understanding. For organizations with Premium, Copilot is the better choice for new deployments. For Pro-only environments, well-configured Q&A delivers significant value.

Related Resources

• Q&A to Copilot Migration
• AI Features in Power BI 2025
• Power BI Copilot Best Practices
• Power BI Training