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
Run your data team as a product team
Data teams can significantly improve their stature and abilities in an organization, when they work with a product mindset. Product teams typically have UX experts, Designers, Product Managers, Engineering Managers and more, involved in the process of generating new features that will delight their customers.
In this talk, we'll argue that Data teams should take on a very similar mindset when leading and growing their data org. We'll make the case that this mindset can scale from a single person team to a large organization. We'll share what this looks like on the ground and in the day to day.
Attendees will be able to walk away feeling empowered about the vital role the data team should — and can — play in every organization. They will explore a new mental framework for how to think about all of the data related activities in their organization.
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Last modified on: Nov 29, 2023