Table of Contents

Culture & teams
• • No silver bullets: Building the analytics flywheel
• • Identity Crisis: Navigating the Modern Data Organization
• • Scaling Knowledge > Scaling Bodies: Why dbt Labs is making the bet on a data literate organization
• • Down with 'data science'
• • Refactor your hiring process: a framework
• • Beyond the Box: Stop relying on your Black co-worker to help you build a diverse team
• • To All The Data Managers We've Loved Before
• • From Diverse "Humans of Data" to Data Dream "Teams"
• • From 100 spreadsheets to 100 data analysts: the story of dbt at Slido
• • New Data Role on the Block: Revenue Analytics
• • Data Paradox of the Growth-Stage Startup
• • Share. Empower. Repeat. Come learn about how to become a Meetup Organizer!
Data futures
• • Keynote: How big is this wave?
• • Analytics Engineering Everywhere: Why in the Next Five Years Every Organization Will Adopt Analytics Engineering
• • The Future of Analytics is Polyglot
• • The modern data experience
• • Don't hire a data engineer...yet
• • Keynote: The Metrics System
• • This is just the beginning
• • The Future of Data Analytics
• • Coalesce After Party with Catalog & Cocktails
Frameworks & best practices
• • The Operational Data Warehouse: Reverse ETL, CDPs, and the future of data activation
• • Built It Once & Build It Right: Prototyping for Data Teams
• • Inclusive Design and dbt
• • Analytics Engineering for storytellers
• • When to ask for help: Modern advice for working with consultants in data and analytics
• • Smaller Black Boxes: Towards Modular Data Products
• • Optimizing query run time with materialization schedules
• • How dbt Enables Systems Engineering in Analytics
• • Operationalizing Column-Name Contracts with dbtplyr
• • Building On Top of dbt: Managing External Dependencies
• • Data as Engineering
• • Automating Ambiguity: Managing dynamic source data using dbt macros
• • Building a metadata ecosystem with dbt
• • Modeling event data at scale
• • Introducing the activity schema: data modeling with a single table
• • dbt in a data mesh world
• • Sharing the knowledge - joining dbt and "the Business" using Tāngata
• • Eat the data you have: Tracking core events in a cookieless world
• • Getting Meta About Metadata: Building Trustworthy Data Products Backed by dbt
• • Batch to Streaming in One Easy Step
Tool deep dives
• • dbt 101: Stories from real-life data practitioners + a live look at dbt
• • The Modern Data Stack: How Fivetran Operationalizes Data Transformations
• • Implementing and scaling dbt Core without engineers
• • dbt Core v1.0 Reveal ✨
• • Data Analytics in a Snowflake world
• • Firebolt Deep Dive - Next generation performance with dbt
• • The Endpoints are the Beginning: Using the dbt Cloud API to build a culture of data awareness
• • dbt, Notebooks and the modern data experience
• • You don’t need another database: A conversation with Reynold Xin (Databricks) and Drew Banin (dbt Labs)
Workshops
• • Git for the rest of us
• • How to build a mature dbt project from scratch
• • Tailoring dbt's incremental_strategy to Artsy's data needs
• • Observability within dbt
• • The Call is Coming from Inside the Warehouse: Surviving Schema Changes with Automation
• • So You Think You Can DAG: Supporting data scientists with dbt packages
• • How to Prepare Data for a Product Analytics Platform
• • dbt for Financial Services: How to boost returns on your SQL pipelines using dbt, Databricks, and Delta Lake
• • Stay Calm and Query on: Root Cause Analysis for Your Data Pipelines
• • Upskilling from an Insights Analyst to an Analytics Engineer
• • Building an Open Source Data Stack
• • Trials and Tribulations of Incremental Models