The modern data platform elegantly consists of a complex set of elements. It must manage data from multiple source systems existing in different locations that are matched, consolidated, controlled, and packaged with business logic within an infrastructure of varied technologies strung together. Providing evidence and trust, an observability platform with dbt as the hub monitors ELT down to the individual processes. It ensures that SLAs are met regarding availability, throughput, and quality. Come see how Slalom confidently assures the user community that the democratized data there meets organizational standards.

Check Notion document here: https://montrealanalytics.notion.site/Coalesce-Workshop-Guide-6382db82046f41599e9ec39afb035bdb

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

As analytics engineers and data people, we know the value we create in our own blood, sweat, and dbt models. But how is this value actually realized in practice? In this talk, David Jayatillake (Metaplane) draws on his experiences to discuss the processes, ways of thinking, tooling, and governance needed to realize the benefits from analytics engineering work in the greater organization.

Check the slides here: https://docs.google.com/presentation/d/1VmmqNQsrv1t0uuV81O6PJQ1XASyLRGxvAdB8eWIG9TQ/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

How do you train and enable 20 data analysts to use dbt Core in a short amount of time?

At M1, engineering and analytics are far apart on the org chart, but work hand-in-hand every day. M1 engineering has a culture that celebrates open source, where every data engineer is trained and empowered to work all the way down the infrastructure stack, using tools like Terraform and Kubernetes. The analytics team is comprised of strong SQL writers who use Tableau to create visualizations used company wide. When M1 knew they needed a tool like dbt for change management and data documentation generation, they had to figure out how to bridge the gap between engineering and analytics to enable analysts to contribute with minimal engineering intervention. Join Kelly Wachtel, a senior data engineer at M1, explain how they trained about 20 analysts to use git and dbt Core over the past year, and strengthened their collaboration between their data engineering and analytics teams.

Check the slides here: https://docs.google.com/presentation/d/1CWI97EMyLIz6tptLPKt4VuMjJzV_X3oO/edit?usp=sharing&ouid=110293204340061069659&rtpof=true&sd=true

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Participants in the dbt Labs partnership program are invited to a partner-only event on Monday, October 17th to hear what’s new on our product and company roadmap, learn about our partner programs, and meet the dbt Labs team and colleagues at other partner companies.

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

As organizations continue scaling their data investments, analytics practitioners are increasingly getting exposed to more areas of the business. In the process, they are learning that often times there are discrepancies in how key business metrics are being defined across teams. After encountering this first hand in her transition from business operations to product analytics, Nadja Jury (Education Perfect) became curious to learn how others were navigating this reality and set out to on a research mission. Nadja joins us at Coalesce to share her learnings from the field, and build more community around the conversation.

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.