✦ AI Use Case

Copilot for Azure Data
Natural Language to SQL

How Microsoft Copilot in Azure Data Studio enables business analysts to query SQL Server databases in plain English — no SQL knowledge required.

🏚 Industry: Business Intelligence
🛠 Tool: Copilot in Azure Data Studio
Impact: Self-service SQL for non-developers

Business Problem

Scenario: Analyst SQL Dependency Bottleneck

Business analysts submit 30-40 ad-hoc data requests per week to the database team. Each request takes 1-3 days to fulfill. Analysts know what data they need but cannot write SQL. The database team is overwhelmed with simple queries that distract from complex development work.

Copilot NL-to-SQL Examples

Natural Language Input
"Show me total sales by product category for Q4 2025,
compared to Q4 2024, sorted by biggest growth"
Copilot-Generated T-SQL
SELECT
    p.Category,
    SUM(CASE WHEN YEAR(o.OrderDate)=2025 AND DATEPART(q,o.OrderDate)=4
             THEN oi.LineTotal ELSE 0 END) AS Q4_2025,
    SUM(CASE WHEN YEAR(o.OrderDate)=2024 AND DATEPART(q,o.OrderDate)=4
             THEN oi.LineTotal ELSE 0 END) AS Q4_2024,
    SUM(CASE WHEN YEAR(o.OrderDate)=2025 AND DATEPART(q,o.OrderDate)=4
             THEN oi.LineTotal ELSE 0 END) -
    SUM(CASE WHEN YEAR(o.OrderDate)=2024 AND DATEPART(q,o.OrderDate)=4
             THEN oi.LineTotal ELSE 0 END) AS YoY_Growth
FROM Orders o
JOIN OrderItems oi ON o.OrderID = oi.OrderID
JOIN Products p ON oi.ProductID = p.ProductID
GROUP BY p.Category
ORDER BY YoY_Growth DESC;
Schema-aware generation: Copilot reads your actual database schema — table names, column names, relationships — and generates syntactically correct SQL that references your real objects. It also explains the query in plain English so analysts can learn SQL progressively.

Measured Outcomes

40
Weekly analyst requests eliminated
3 days
Wait time reduced to 3 minutes
8
Analysts now self-sufficient in SQL
100%
DB team time freed for dev work
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