SQL Data Access Use Case - Naftiko Blog

Title

• SQL Data Access

Tagline

• Data lives in silos. Teams want insights now but every new API means another custom connector.

Body

This use case seeks to consistently unlock the data companies currently depend upon across multiple third-party SaaS providers and a variety of existing database connections via JDBC and ODBC to ensure AI integrations have the data they require. Data today is spread across many internal and external systems, and making it consistently available as part of AI integrations has significantly slowed the delivery of new products and features.

Teams benefit from consistent SQL access to data sources via ODBC/JDBC interfaces, and expanding this access to third-party SaaS will help teams provide the context, resources, tooling, and data needed to deliver AI integrations across the enterprise. The capability and resulting engine deployment for this use case provides a unified, consolidated, and simplified approach to providing the data needed to power individual AI integrations within specific business domains.

Tags

• SQL
• Data
• SaaS
• Dashboards
• Analytics
• Copilots

Benefits

• Unlock SaaS data
• JDBC / ODBC drivers
• Federated SQL processing

Pain

• Limited or No Access to SaaS Data for Analytics Teams
• No Access to Data Sources Across MCP-Enabled AI Integration
• Demand for 3rd-Party Data for Business Intelligence in Dashboards
• Demand for 3rd-Party Data by Data Science for ML Engineering

Gains

• Access to SaaS Data via SQL
• Access to Internal APIs via SQL
• Easy Connections to Existing Dashboards
• Plug-and-Play Connectors for Data Science

Connects

• Internal APIs
• Infrastructure APIs
• SaaS APIs
• Partner APIs
• Legacy APIs

Adapters

• HTTP
• OpenAPI
• ODBC
• JDBC
• MCP

Links

• GitHub Issue
• Google Doc