When and how to adopt dbt
About the session:
So you’re finally getting the hang of testing with dbt—that’s great! But how do you go from the occasional ❌ in your tests to having an actual plan to keep your pipelines running smoothly?
Check out dbt Labs as we explore when and how to adopt dbt Cloud with the simplicity and power of the Snowflake Data Cloud. Each session shows the why and how behind scaling dbt capabilities to production readiness. Watch the recording of this first session now, as we discuss how to operationalize data testing with Randy Pitcher, Sr Solutions Architect at dbt Labs.
What you’ll hear:
- How organizations have built the case for dbt Cloud
- How to decide when it is time to add ongoing monitoring and alerting with dbt Cloud
- The actual business problems that are caused by having low visibility and immature operations when data breaks
- How dbt tests solve part of this problem with accessible data quality features for the busy data engineer or time-constrained analyst
Who’s this for:
- Users of open source dbt who are interested in understanding the benefit and value of dbt Cloud.
- Managers of data teams either using or considering using dbt and are curious to learn more about data quality and observability. How does it work? Is this worth doing? Why not just keep doing what you’re doing?
- Executive decision-makers under pressure to deliver more data products with stricter budgets. Can you afford a pipeline failure the night before the highest revenue day of your year? What updates do you have for your stakeholders about how you are making sure your teams are delivering high-quality outcomes and spending less at the same time?
We hope you’ll join us for an outcomes-focused session about scaling data quality at your organization with no magic🪄, black boxes, or fairytales—just proven practices your competitors are already implementing today.