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 [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 [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 [https://www.linkedin.com/in/cfiore11/], Sr. Data Analyst @ dbt Labs
* Paige Berry [https://www.linkedin.com/in/paigeacberry/], Lead Data Analyst @ dbt Labs
* Logan Cochran [https://www.linkedin.com/in/lcochran400/], Data Analyst @ dbt Labs
* Jules Arombo [https://www.linkedin.com/in/julianarombo/], Analytics Engineer @ dbt Labs
Created and Produced by:
* Bolaji Oyejide [https://www.linkedin.com/in/bolaji/], Community Manager @ dbt Labs
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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.
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