22-25 April 2026 
AI for Developers, Not End Users: Master Agentic BI Development Workflows
50+50 minute session for SQLBits 2026Thursday - 01 Jan 1970 - 01:00 - 01:00TL; DR
Transform BI development with AI agents that build, test, and maintain your analytics stack autonomously. Master agentic workflows orchestrating specialized agents for data pipelines, semantic models, and Power BI reports.
Session Details
End-user AI tools answer questions. Developer AI orchestrates specialized agents that build, test, and maintain your entire analytics stack. Discover the fundamental difference between AI copilots for report consumers and agentic workflows that transform how BI developers work with Data Pipeline, Databases, Power BI Semantic Layers and Reports.
What you'll master:
- Architect multi-agent BI workflow: where specialized subagents handle data transformation, semantic modeling, and report development autonomously
- Leverage MCP servers: providing AI agents direct access to SQL Server schemas, Power BI workspaces, and development environments
- Build intelligent development pipelines: where agents detect data model changes, generate migration scripts, update semantic layers, and maintain report consistency automatically
- Create portable skills: packaging DAX patterns, SQL optimization techniques, and BI best practices into reusable agent expertise
- Design specialized subagents: for code review, testing DBT pipelines, validating TMDL semantic layers, and generating PBIR reports end-to-end
Experience live demonstrations: watch AI agents build complete BI solutions from raw data through data transformations to Power BI TMDL semantic models and PBIR reports—showcasing developer-grade AI orchestration, not simple chat interfaces.
Position yourself at the forefront where BI developers orchestrate agent teams rather than manually coding every transformation, measure, and visual.
Part 2
What you'll master:
- Architect multi-agent BI workflow: where specialized subagents handle data transformation, semantic modeling, and report development autonomously
- Leverage MCP servers: providing AI agents direct access to SQL Server schemas, Power BI workspaces, and development environments
- Build intelligent development pipelines: where agents detect data model changes, generate migration scripts, update semantic layers, and maintain report consistency automatically
- Create portable skills: packaging DAX patterns, SQL optimization techniques, and BI best practices into reusable agent expertise
- Design specialized subagents: for code review, testing DBT pipelines, validating TMDL semantic layers, and generating PBIR reports end-to-end
Experience live demonstrations: watch AI agents build complete BI solutions from raw data through data transformations to Power BI TMDL semantic models and PBIR reports—showcasing developer-grade AI orchestration, not simple chat interfaces.
Position yourself at the forefront where BI developers orchestrate agent teams rather than manually coding every transformation, measure, and visual.
Part 2
3 things you'll get out of this session
What you'll master:
- Architect multi-agent BI workflow: where specialized subagents handle data transformation, semantic modeling, and report development autonomously
- Leverage MCP servers: providing AI agents direct access to SQL Server schemas, Power BI workspaces, and development environments
- Build intelligent development pipelines: where agents detect data model changes, generate migration scripts, update semantic layers, and maintain report consistency automatically
- Create portable skills: packaging DAX patterns, SQL optimization techniques, and BI best practices into reusable agent expertise
- Design specialized subagents: for code review, testing DBT pipelines, validating TMDL semantic layers, and generating PBIR reports end-to-end
- Architect multi-agent BI workflow: where specialized subagents handle data transformation, semantic modeling, and report development autonomously
- Leverage MCP servers: providing AI agents direct access to SQL Server schemas, Power BI workspaces, and development environments
- Build intelligent development pipelines: where agents detect data model changes, generate migration scripts, update semantic layers, and maintain report consistency automatically
- Create portable skills: packaging DAX patterns, SQL optimization techniques, and BI best practices into reusable agent expertise
- Design specialized subagents: for code review, testing DBT pipelines, validating TMDL semantic layers, and generating PBIR reports end-to-end
Speakers
Scott Bell's other proposed sessions for 2026
AI Security in Practice: How to run Threat Modeling Workshops - 2026
Building Context, Not Vibes Pratical AI Augmented Data Engineering - 2026
Building Context, Not Vibes Pratical AI Augmented Data Engineering - Part 1 - 2026
Building Context, Not Vibes Pratical AI Augmented Data Engineering (Part 2) - 2026
Danger in Delegation: When “Helpful” Becomes Harmful - 2026
Optimizing Your Delta Lake: Beyond the Defaults - 2026
Scott Bell's previous sessions
Navigating Data Governance in the Age of Generative AI
In the rapidly evolving world of data analytics, the emergence of Large Language Models (LLMs) has sparked a debate: Are LLMs signaling the end of traditional data analytics? This session delves into the heart of this question, exploring the fundamental workings of LLMs and their transformative impact on the analytics landscape. Attendees will gain insights into the advantages and potential pitfalls of integrating LLMs into their data strategies. We'll discuss the innovative use cases LLMs unlock and emphasize the paramount importance of governance and lineage in harnessing their full potential. Whether you're intrigued by the brilliance of LLMs or wary of their implications, this session will equip you with a balanced perspective to navigate the future of data analytics.
Cosmos 101
Find out everything you need to know to get started with Azure Cosmos DB in 20 minutes or less.
Is HTAP the future?
Hybrid Transactional Analytical Processing solve the age old problem of integrating operational processes with analytical capabilities within a single system. Find out what they're and how they deliver value
