2: The future of data analytics at dbt Labs
In this episode of the Data Analyst Show, the hosts discuss their experiences with new features at dbt, particularly focusing on the Insights feature, Co-Pilot, and Canvas. They share how these tools enhance their workflows, improve documentation, and facilitate collaboration among data teams. The conversation highlights the importance of cost management in data operations and the benefits of a visual approach to data modeling, making analytics more accessible to non-technical stakeholders. Read the dbt Launch Showcase 2025 recap https://www.getdbt.com/blog/dbt-launch-showcase-2025-recap Watch the webinar on demand https://www.getdbt.com/resources/webinars/2025-dbt-cloud-launch-showcase Takeaways dbt Insights feature allows for easier data exploration and analysis. Bookmarking queries in Insights promotes intentional documentation. dbt Co-Pilot helps automate documentation, saving time for analysts. dbt Canvas provides a visual interface for data modeling, making it accessible to non-SQL users. Cost management features help teams understand the financial implications of their data operations. Collaboration is enhanced through shared insights and documentation. The integration of tools within dbt streamlines workflows for analysts. Using Canvas can improve project management and stakeholder communication. The ability to self-serve data insights empowers stakeholders. Continuous feedback from analysts shapes the development of dbt features. Chapters 00:00: Introduction to Data Analysis and dbt Labs Tools 01:53: Insights Feature: Enhancing Data Analysis Workflows 04:21: Handling Data Outages and Using Insights Effectively 06:28: Bookmarking and Sharing Queries for Collaboration 09:09: The Role of Documentation in Data Analysis 11:44: Exploring Canvas: A Visual Tool for Model Building 14:28: Self-Service Data Exploration with Canvas 16:55: Integrating Stakeholder Needs into Data Models 20:12: Project Management in Analytics 22:25: Collaborative Data Modeling 24:45: Ecosystem of Features in dbt 27:45: User Feedback and Product Development 29:08: Cost Management in Data Operations 33:35: Ensuring Data Quality and Efficiency Hosted by: Chris Fiore, Sr. Data Analyst @ dbt Labs Paige Berry, Lead Data Analyst @ dbt Labs Logan Cochran, Data Analyst @ dbt Labs Jules Arombo, Analytics Engineer @ dbt Labs Created and Produced by: Bolaji Oyejide, Community Manager @ dbt Labs — About the dbt Community: We’ve always believed the best way to get better at data is by sharing what you’re learning. That’s why we built the dbt Community—a place where data pros at every level can ask questions, debate ideas, and push each other forward. It’s not just about solving today’s problems—it’s about building what’s next, together. dbt Community - for and by data pros. Build reliable transformation pipelines. Test & deploy models. Optimize queries. Structure data for self-serve analysis. Come hang out and transform with 70,000 of the brightest Analytics Engineers, Data Engineers, Data Analysts, and Data Scientists in the world Join the dbt Community
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