Azure SQL Integration | Database Analytics Made Easy

Connect Azure SQL and let AI agents query customer records, transactions, and KPIs alongside marketing data from 500+ platforms.

SOC 2 Type II 1,000+ data sources Any warehouse or BI tool

Improvado Agent

Connected to Azure SQL

Show me the top 5 tables by row count in the marketing database and their last update timestamps.

Your marketing database contains 847M rows across 23 tables. The largest table is customer_events with 312M rows, last updated 4 minutes ago. Sessions table has 189M rows, updated 12 minutes ago.

Check query performance for the daily revenue rollup job and flag any tables with stale data older than 2 hours.

The revenue_daily_agg query executed in 8.3 seconds with 2.1M rows scanned. Found 3 tables with stale data: campaign_costs last updated 3.2 hours ago, ad_impressions 4.7 hours ago, conversion_events 2.8 hours ago.

Trusted by data-driven teams

1,000+

Integrations

200+

Azure SQL Fields

99.9%

SLA Uptime

<5 min

Setup

SOC 2

Type II

Key Takeaways

Connect Azure SQL Database integration

Improvado connects directly to your Azure SQL Database through secure API protocols. Our platform extracts table data, stored procedures, and custom queries on your defined schedule. Data refreshes automatically every 15 minutes to 24 hours based on your requirements. No manual exports or CSV uploads needed.

200+ metrics and dimensions Campaigns, ad groups, keywords, audiences, geo, device — all granularity levels from the Azure SQL API

15-minute refresh cycles Near real-time sync with 99.9% SLA uptime. No stale dashboards.

Cross-channel normalization Marketing CDM unifies your data with 1,000+ sources into one schema. No manual mapping.

Any warehouse or BI tool Snowflake, BigQuery, Redshift, Databricks, Power BI, Tableau, Looker Studio

AI Agent access via MCP Query, write, and monitor Azure SQL through Claude, ChatGPT, Cursor, or any MCP client

Enterprise-grade security SOC 2 Type II, HIPAA, GDPR, CCPA. Raw data never leaves your environment.

OAuth setup in under 5 minutes No API keys, no code, no developer setup. Schema changes handled automatically.

Zero ongoing maintenance Pagination, rate limits, API versioning — all managed. Your team focuses on analysis.

Integration Details

Unified data across platforms

Improvado's Marketing Common Data Model normalizes your Azure SQL data alongside 500+ other sources. Customer records, transaction data, and business metrics flow into standardized schemas. Your Azure SQL tables join seamlessly with marketing platforms like Google Ads, Facebook, and Salesforce. Cross-platform analysis becomes possible without complex data engineering.

Azure SQL Database · SQL auth/Azure AD · 15-min sync · incremental + full · TDS protocol

Schema Overview

Data objects and fields Improvado extracts from Azure SQL

Object	Fields
Tables	table_catalog table_schema table_name table_type created_date modified_date
Columns	table_name column_name ordinal_position data_type character_maximum_length is_nullable
Indexes	table_name index_name index_type is_unique is_primary_key column_name
Views	view_catalog view_schema view_name view_definition check_option is_updatable
Constraints	constraint_catalog constraint_schema constraint_name constraint_type table_name is_deferrable

How it works

From connection to autonomous action in three steps

Connect

Connect via SQL Server authentication or Azure Active Directory. Provide server endpoint, database name, and credentials with read permissions for monitoring or write permissions for optimization actions. Connection validates schema access and query execution rights.

Ask

Ask questions like 'Which tables have grown most in the last week' or 'Show me slow-running queries consuming over 10 seconds' or 'What indexes are missing on high-traffic tables'.

Act

The agent creates indexes on frequently queried columns, archives old partition data, updates table statistics for query optimization, kills long-running queries blocking resources, and adjusts database scaling tiers based on load patterns.

Use Cases

What teams ask their AI agent about Azure SQL

Real prompts from enterprise marketing teams. The agent reads your data, answers in seconds, and takes action when you ask.

See how teams use Improvado →

Improvado Agent Analysis

Combine Azure SQL customer data with Google Ads performance for complete attribution analysis

Your AI agent analyzes Azure SQL data and delivers actionable insights — automatically, in seconds.

6 hrs → 20 min

Improvado Agent Cross-channel

Merge transaction records with marketing spend to calculate true customer lifetime value

Your AI agent analyzes Azure SQL data and delivers actionable insights — automatically, in seconds.

Manual → auto

Improvado Agent Reporting

Build executive dashboards combining database KPIs with marketing performance metrics

Your AI agent analyzes Azure SQL data and delivers actionable insights — automatically, in seconds.

4 hrs → 30 min

AI Agent Access

Your agent joins Azure SQL tables with every marketing campaign

Read

Reads table schemas, row counts, storage sizes, index configurations, query execution plans, performance metrics, connection pool stats, replication lag, backup status, and partition metadata across all databases in your Azure SQL instance.

Write

Writes by creating and dropping indexes, updating statistics, archiving partitions, killing blocking queries, adjusting compute tiers, configuring auto-scaling rules, setting up query store parameters, and modifying connection timeout settings.

Monitor

Monitors query execution times exceeding thresholds, storage capacity approaching limits, connection pool exhaustion, replication delays, index fragmentation levels, blocking query chains, failed backup jobs, and CPU utilization spikes during peak hours.

The AI agent queries customer transaction history, product sales, and database KPIs, then correlates them with Google Ads spend and campaign performance. It can calculate true customer lifetime value by acquisition channel, identify which campaigns drive repeat purchases, and explain revenue changes by matching database records with ad exposure. Ask it to find high-value customer segments and their acquisition costs.

Claude ChatGPT Cursor Gemini Any MCP Client

Explore MCP →

Improvado Agent · Azure SQL

You

Show me database storage usage and query performance for the last 24 hours

Database Performance

Table	Storage (GB)	Avg Query Time
customer_orders	127.4 GB	2.1s (-18%)
product_inventory	89.2 GB	1.4s (-12%)
shipment_tracking	156.8 GB	3.7s (+9%)
payment_transactions	203.5 GB	1.9s (-22%)
customer_sessions	341.1 GB	4.2s (+14%)

5 tables · 918 GB total · avg 2.7s query time

You

Create an index on shipment_tracking.order_id to improve join performance

Index Created Successfully

Query time reduced from 3.7s to 1.2s (68% faster)

Destinations

Send Azure SQL data anywhere

Load normalized data to your preferred warehouse, BI tool, or cloud storage. Click any destination to see its integration guide.

Snowflake → BigQuery → Redshift → Databricks → Power BI → Tableau → Looker Studio → Google Sheets → Domo → Excel → Qlik → Amazon S3 → Metabase → Grafana → PostgreSQL → Azure SQL →

SOC 2 Type II: Certified Security

HIPAA: Health Data Privacy

GDPR: EU Data Protection

CCPA: CA Privacy Standard

Compare

They extract data. Improvado deploys an agent.

Traditional tools move data from A to B. Improvado gives you an AI agent that reads, acts, and monitors — with Azure SQL as one of 1,000+ integrated sources.

Feature	Improvado	Supermetrics	Funnel.io	Fivetran
Data fields extracted	200+	~90	~120	~80
Total integrations	1,000+	~150	~500	~300
Cross-channel normalization (CDM)	✓ Built-in	✗ Manual	Basic mapping	✗ Raw only
AI Agent access (MCP)	✓ Read, Write, Monitor	✗	✗	✗
Data warehouse destinations	✓ 16+ warehouses & BI tools	Sheets, Looker, BigQuery	BigQuery, Snowflake, Redshift	✓ Broad warehouse support
Refresh frequency	Every 15 min	Scheduled triggers	Daily / 6hr	Every 15 min (premium)
SOC 2 Type II & HIPAA	✓	✗ SOC 2 only	✓ SOC 2	✓
Best for	Teams that want an AI agent, not a pipeline	Small teams, spreadsheets	Mid-market, data teams	Engineering-led ELT pipelines

Comparison based on publicly available documentation as of April 2026. Feature availability may vary by plan tier.

FAQ

Frequently asked questions

How does Improvado connect to Azure SQL Database?

Improvado uses secure database connectors with SSL encryption to access your Azure SQL instance. You provide connection credentials and specify which tables or queries to extract. Our platform handles all authentication and data transfer protocols automatically.

What Azure SQL data can Improvado extract?

Improvado extracts tables, views, stored procedures, and custom SQL queries from your Azure SQL Database. We support all standard data types including VARCHAR, INT, DATETIME, and JSON fields. Complex joins and aggregations are handled during the extraction process.

How often does Azure SQL data refresh in Improvado?

Data refresh intervals range from 15 minutes to 24 hours depending on your plan and requirements. Most customers set hourly or daily refreshes for transactional data. Real-time streaming is available for enterprise customers with high-volume databases.

Can Improvado handle large Azure SQL databases?

Yes, Improvado processes databases with millions of records through incremental loading and parallel processing. We extract only new or updated records after the initial full sync. Large table extractions are optimized to minimize impact on your database performance.

Which destinations work with Azure SQL data?

Azure SQL data loads into BigQuery, Snowflake, Redshift, and other cloud warehouses. Business intelligence tools like Tableau, Power BI, and Looker connect directly to your normalized datasets. The data maintains referential integrity across all destination platforms.

Does Improvado transform Azure SQL data during extraction?

Improvado applies data transformations including column mapping, data type conversion, and schema standardization. Custom business logic and calculated fields can be added during the ETL process. All transformations follow our Marketing Common Data Model for consistency with other data sources.

Customer stories

See all customer stories →

“Improvado saves about 90 hours per week and allows us to focus on data analysis rather than routine data aggregation, normalization, and formatting.”

Jeff LeeHead of Social, Media Buy, Influencer & Marketing Data, ASUS

Read story →

“Improvado's reporting tool effortlessly integrates all our marketing data so we can easily track users across their entire digital journey. This saves me and my team countless hours.”

Marc CerniglioInsights & Automation Manager, Chacka Marketing

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