AI-Powered Data Analytics Using BlazeSQL and SQL Server equips data professionals with the knowledge and practical skills to use BlazeSQL with Microsoft SQL Server for AI-assisted SQL generation, data analysis, reporting, and business intelligence.
Duration 3 Days – 21 hrs.
Overview
The AI-Powered Data Analytics Using BlazeSQL and SQL Server Training Course is a comprehensive, hands-on program designed to help professionals leverage Artificial Intelligence to simplify SQL querying, accelerate business analytics, and improve decision-making. Participants will learn how to use BlazeSQL, an AI-powered SQL assistant, to transform natural language questions into accurate SQL queries against Microsoft SQL Server databases.
The course covers the complete workflow from securely connecting BlazeSQL to SQL Server, exploring database schemas, generating and validating AI-created SQL queries, and producing meaningful business insights through AI-assisted reporting. Participants will also learn prompt engineering techniques, enterprise governance considerations, query validation, and best practices for integrating AI-powered analytics into daily business operations.
Through practical workshops and a capstone project, attendees will gain real-world experience using BlazeSQL to analyze sales, customer, inventory, and operational data while producing executive-ready reports and recommendations.
Objectives
- Understand the concepts and architecture of AI-powered SQL analytics.
- Connect BlazeSQL securely to Microsoft SQL Server databases.
- Use natural language to generate SQL queries.
- Validate and optimize AI-generated SQL statements.
- Apply prompt engineering techniques to improve query accuracy.
- Perform business analytics using AI-generated SQL.
- Generate executive summaries and business insights from query results.
- Identify trends, anomalies, and operational KPIs using BlazeSQL.
- Implement best practices for AI governance, security, and data privacy.
- Integrate BlazeSQL into enterprise reporting and self-service analytics workflows.
- Deliver actionable recommendations through AI-assisted data analysis.
Target Audience
- Database Administrators
- Business Analysts
- Data Analysts
- Business Intelligence (BI) Developers
- SQL Developers
- Decision Makers
- Reporting Analysts
- Data Engineers
- IT Professionals responsible for analytics and reporting
Prerequisites
- Basic SQL knowledge
- Basic understanding of Microsoft SQL Server databases
- Familiarity with relational database concepts
- Basic experience creating SQL queries is recommended
Course Outline
Day 1 – Getting Started with BlazeSQL
Module 1: Introduction to AI-Powered SQL Analytics
- Challenges in traditional SQL reporting
- What is an AI SQL Agent?
- Overview of BlazeSQL
- BlazeSQL architecture and workflow
- Supported databases
- Comparing BlazeSQL with traditional SQL development
Module 2: Connecting BlazeSQL to SQL Server
- Connecting BlazeSQL to SQL Server
- Read-only database access
- Database schema discovery
- Managing credentials securely
- Understanding tables, views, and relationships
- Preparing SQL Server for AI-assisted analytics
Module 3: Natural Language to SQL with BlazeSQL
- Asking business questions in plain English
- How BlazeSQL generates SQL
- Reviewing generated SQL
- Explaining SQL statements
- Refining AI-generated queries
- Understanding AI limitations
Hands-on Workshop
- Connect BlazeSQL to SQL Server
- Explore the database schema
- Generate SQL using natural language
- Explain generated SQL
- Validate results in SQL Server
Day 2 – Business Analytics Using BlazeSQL
Module 4: Prompt Engineering for Better Analytics
- Writing effective prompts
- Adding business context
- Using database schema effectively
- Improving query accuracy
- Reusable prompt templates
Module 5: Business Intelligence with BlazeSQL
- Sales performance
- Customer behavior
- Inventory movement
- Product profitability
- Revenue trends
- Operational KPIs
Module 6: AI-Powered Reporting
- Summarizing query results
- Executive summaries
- Trend analysis
- Root cause analysis
- Identifying anomalies
- Data storytelling
Hands-on Workshop
- What are our top-selling products?
- Which customers contribute the most revenue?
- Which products have declining sales?
- What inventory requires replenishment?
- Which regions perform best?
Day 3 – Advanced BlazeSQL Workflows
Module 7: Best Practices for Enterprise Use
- Validating AI-generated SQL
- Query optimization
- Data privacy and security
- Read-only access strategies
- AI governance
- Common mistakes
Module 8: Integrating BlazeSQL into Business Processes
- Daily reporting workflows
- Self-service analytics
- Supporting management decisions
- Working alongside BI tools
- When to use AI versus manual SQL
Module 9: Capstone Workshop – AI Analytics Project
Participants use BlazeSQL with a real SQL Server database to:
- Connect to the database
- Explore the schema
- Ask business questions in natural language
- Generate and validate SQL
- Analyze results
- Produce executive summaries
- Present insights and recommendations
