Table of Contents
- Data transformation
- • Kiro Dreams of Data
- • dbt 101 (EU and US-friendly)
- • Ask the experts: Customer product journey
- • How to build a reputation on more than just dashboards
- • Ask the experts: Version controlling your metrics
- • How to complete a data modeling project at a $6B company
- • Kimball in the context of the modern data warehouse: what's worth keeping, and what's not
- • Seven use cases for dbt
- • Quickstart your analytics with Fivetran dbt packages
- • Building a marketing attribution model with dbt
- Data testing
- Implementations + deployment
- Documentation + metadata
- The modern data stack
- Data dream teams
- • Lessons in prioritization: How to balance the 'quick questions' against your team's long-term plan
- • Getting started with technical blogging
- • How to structure a data team
- • Run your data team as a product team
- • Hiring a diverse data team
- • How to start your analytics engineering team
- • Supercharging your data team
- • Balancing creativity and proficiency as a data team
- • Evaluating an offer in the data space
- • Taking off with dbt: JetBlue's dbt journey!
- • Data dream teams: TripActions
- • Data dream teams: Netlify
Taking off with dbt: JetBlue's dbt journey!
Here's some facts about JetBlue's dbt project — they have 1800 models, on top of 280 data sources, have defined 8500 tests and they built their entire dbt project in six months!
In this session, Ashley will share how a small team of data engineers successfully migrated their entire [data warehouse](https://docs.getdbt.com/terms/data-warehouse) workload to dbt, and their tips for setting up your dbt project for success.
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Last modified on: Oct 11, 2022