Meet Select Star at dbt Coalesce!

Founded in 1952, nib has become one of Australia's fastest growing health funds, leveraging advanced data practices to drive its expansion. With dozens of dbt projects and thousands of dbt models interacting across the organization, the data team has built processes and frameworks to effectively govern these models. We will talk through the organic growth of dbt at nib — now at 70 active users, from analytics engineers to data analysts — outlining how the team uses meta tags, metadata analysis, and data lineage to manage changes and enhance data accessibility. We will also discuss the internal processes developed at nib that promote democratization and collaboration in our analytics engineering team.

In this talk, we explore the challenges and strategies of data teams that have scaled their dbt over 1,000 models and often across multiple projects. We'll dive into the types of organizations that reach this scale and the common challenges they face. From data democratization efforts to infrastructure and tooling requirements, we'll cover what it takes to effectively manage such a vast and complex dbt environment. What does their team structure look like? What type of processes do they have? What type of automation did they implement to enable efficient data operations at scale? Whether you're just starting with dbt or looking to manage a growing number of models, this talk is to offer practical insights to help you navigate the complexities of large-scale dbt deployments.