The Future of Business Intelligence:
Looker Semantic Layer + FinOps in BigQuery

Discover why the traditional approach to BI is failing and how a new paradigm combining semantic governance with cost optimization is reshaping the industry.

• The silent transformation happening in Business Intelligence
• Why technology alone is not enough without proper architecture
• The three pillars of modern BI: semantic layer, FinOps, and AI
• What this means for data teams in 2025 and beyond

A deep dive into the technology stack, architecture patterns, and implementation strategies that are redefining modern Business Intelligence platforms.

• Complete technology stack breakdown (BigQuery, Looker, DBT, AI)
• Reference architecture with detailed layer-by-layer explanation
• Real code examples for intelligent partitioning and clustering
• Looker PDTs with datagroups for smart caching
• AI agent implementation for cost monitoring and optimization

Real-world results from implementing this architecture for an e-commerce company processing 2M+ monthly transactions across three countries.

• From $15,000/month to $6,300/month in BigQuery costs
• 3x performance improvement (45s to 12s dashboard load times)
• 100% metric consistency across all teams
• Complete 5-layer architecture breakdown
• Quantifiable results and lessons learned

A complete implementation framework with design principles, phase-by-phase roadmap, and actionable best practices for BigQuery, Looker, DBT, and FinOps.

• 5-phase implementation roadmap (18-25 weeks)
• Design principles for scalable BI architecture
• 5 proven tips to optimize BigQuery costs
• Looker PDTs: when to use them and when not to
• FinOps for data teams: where to start