Dec 6 - 10, 2021

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Scaling Knowledge > Scaling Bodies: Why dbt Labs is making the bet on a data literate organization

Scaling Knowledge > Scaling Bodies: Why dbt Labs is making the bet on a data literate organization - Erica Louie

Keynote: How big is this wave? Keynote: How big is this wave?

Keynote: How big is this wave? - Martin Casado & Tristan Handy

dbt 101: Stories from real-life data practitioners + a live look at dbt dbt 101: Stories from real-life data practitioners + a live look at dbt

dbt 101: Stories from real-life data practitioners + a live look at dbt - Natty (Jon Natkins) & Alexis Wong Baird

How to build a mature dbt project from scratch

How to build a mature dbt project from scratch - Dave Connors

Analytics Engineering for storytellers

Analytics Engineering for storytellers - Winnie Winship

The modern data experience

The modern data experience - Benn Stancil

Identity Crisis: Navigating the Modern Data Organization Identity Crisis: Navigating the Modern Data Organization Identity Crisis: Navigating the Modern Data Organization Identity Crisis: Navigating the Modern Data Organization Identity Crisis: Navigating the Modern Data Organization

Identity Crisis: Navigating the Modern Data Organization - Jillian Corkin, David Jayatillake, Caitlin Moorman, Barr Moses & Stefania Olafsdottir

Git for the rest of us

Git for the rest of us - Claire Carroll

You don’t need another database: A conversation with Reynold Xin (Databricks) and Drew Banin (dbt Labs) You don’t need another database: A conversation with Reynold Xin (Databricks) and Drew Banin (dbt Labs)

You don’t need another database: A conversation with Reynold Xin (Databricks) and Drew Banin (dbt Labs) - Drew Banin & Reynold Xin

Share. Empower. Repeat. Come learn about how to become a Meetup Organizer!

Share. Empower. Repeat. Come learn about how to become a Meetup Organizer! - Rosie Cardoso

The Operational Data Warehouse: Reverse ETL, CDPs, and the future of data activation

The Operational Data Warehouse: Reverse ETL, CDPs, and the future of data activation - Tejas Manohar

Refactor your hiring process: a framework (Workshop Sponsor) Refactor your hiring process: a framework (Workshop Sponsor) Refactor your hiring process: a framework (Workshop Sponsor)

Refactor your hiring process: a framework (Workshop Sponsor) - Ilse Ackerman, Ezinne Chimah & Rocío Garza Tisdell

Tailoring dbt's incremental_strategy to Artsy's data needs

Tailoring dbt's incremental_strategy to Artsy's data needs - Abhiti Prabahar

Optimizing query run time with materialization schedules

Optimizing query run time with materialization schedules - Ola Canty

How dbt Enables Systems Engineering in Analytics

How dbt Enables Systems Engineering in Analytics - Jorge Cruz Serralles

When to ask for help: Modern advice for working with consultants in data and analytics

When to ask for help: Modern advice for working with consultants in data and analytics - Jacob Frackson

Smaller Black Boxes: Towards Modular Data Products

Smaller Black Boxes: Towards Modular Data Products - Stephen Bailey

The Modern Data Stack: How Fivetran Operationalizes Data Transformations

The Modern Data Stack: How Fivetran Operationalizes Data Transformations - Nick Acosta

Analytics Engineering Everywhere: Why in Five Years Every Organization Will Adopt Analytics Engineering

Analytics Engineering Everywhere: Why in Five Years Every Organization Will Adopt Analytics Engineering - Jason Ganz

Down with

Down with "data science" - Emilie Schario

So You Think You Can DAG: Supporting data scientists with dbt packages

So You Think You Can DAG: Supporting data scientists with dbt packages - Emma Peterson

Operationalizing Column-Name Contracts with dbtplyr

Operationalizing Column-Name Contracts with dbtplyr - Emily Riederer

Data Paradox of the Growth-Stage Startup

Data Paradox of the Growth-Stage Startup - Emily Ekdahl

Batch to Streaming in One Easy Step Batch to Streaming in One Easy Step

Batch to Streaming in One Easy Step - Emily Hawkins & Arjun Narayan

The Call is Coming from Inside the Warehouse: Surviving Schema Changes with Automation The Call is Coming from Inside the Warehouse: Surviving Schema Changes with Automation

The Call is Coming from Inside the Warehouse: Surviving Schema Changes with Automation - Lewis Davies & Erika Pullum

Beyond the Box: Stop relying on your Black co-worker to help you build a diverse team.

Beyond the Box: Stop relying on your Black co-worker to help you build a diverse team. - Akia Obas

Observability Within dbt Observability Within dbt

Observability Within dbt - Kevin Chan & Jonathan Talmi

Inclusive Design and dbt

Inclusive Design and dbt - Evelyn Stamey

Built It Once & Build It Right: Prototyping for Data Teams

Built It Once & Build It Right: Prototyping for Data Teams - Alex Viana

Coalesce After Party with Catalog & Cocktails Coalesce After Party with Catalog & Cocktails

Coalesce After Party with Catalog & Cocktails - Tim Gasper & Juan Sequeda

How to Prepare Data for a Product Analytics Platform (Workshop Sponsor)

How to Prepare Data for a Product Analytics Platform (Workshop Sponsor) - Esmeralda Martinez

Toward a Polyglot Environment for Analytics

Toward a Polyglot Environment for Analytics - Caitlin Colgrove

Automating Ambiguity: Managing dynamic source data using dbt macros

Automating Ambiguity: Managing dynamic source data using dbt macros - Eric Nelson

The Endpoints are the Beginning: Using the dbt Cloud API to build a culture of data awareness

The Endpoints are the Beginning: Using the dbt Cloud API to build a culture of data awareness - Kevin Hu

Data as Engineering

Data as Engineering - Raazia Ali

Building On Top of dbt: Managing External Dependencies

Building On Top of dbt: Managing External Dependencies - Teghan Nightengale

Data Analytics in a Snowflake world: A conversation with Christian Kleinerman and Tristan Handy Data Analytics in a Snowflake world: A conversation with Christian Kleinerman and Tristan Handy

Data Analytics in a Snowflake world: A conversation with Christian Kleinerman and Tristan Handy - Tristan Handy & Christian Kleinerman

Keynote: Building a Force of Gravity

Keynote: Building a Force of Gravity - Drew Banin

dbt Core v1.0 Reveal ✨

dbt Core v1.0 Reveal ✨ - Jeremy Cohen

Firebolt Deep Dive - Next generation performance with dbt Firebolt Deep Dive - Next generation performance with dbt

Firebolt Deep Dive - Next generation performance with dbt - Kevin Marr & Cody Schwarz

dbt, Notebooks and the modern data experience dbt, Notebooks and the modern data experience

dbt, Notebooks and the modern data experience - Allan Campopiano & Elizabeth Dlha

No silver bullets: Building the analytics flywheel No silver bullets: Building the analytics flywheel No silver bullets: Building the analytics flywheel

No silver bullets: Building the analytics flywheel - Kelly Burdine, Lewis Davies & Erika Pullum

Don't hire a data engineer...yet

Don't hire a data engineer...yet - Stefania Olafsdottir

dbt for Financial Services: How to boost returns on your SQL pipelines using dbt, Databricks, and Delta Lake

dbt for Financial Services: How to boost returns on your SQL pipelines using dbt, Databricks, and Delta Lake - Ricardo Portilla

The Future of Data Analytics The Future of Data Analytics The Future of Data Analytics The Future of Data Analytics

The Future of Data Analytics - Sarah Catanzaro, Jennifer Li, Astasia Myers & Julia Schottenstein

Implementing and scaling dbt Core without engineers

Implementing and scaling dbt Core without engineers - Elliot Wargo

Building an Open Source Data Stack

Building an Open Source Data Stack - Katie Hindson

This is just the beginning

This is just the beginning - Alan Cruickshank

dbt in a data mesh world

dbt in a data mesh world - José Cabeda

Introducing the activity schema: data modeling with a single table

Introducing the activity schema: data modeling with a single table - Ahmed Elsamadisi

From Diverse

From Diverse "Humans of Data" to Data Dream "Teams" - Prukalpa Sankar

From 100 spreadsheets to 100 data analysts: the story of dbt at Slido From 100 spreadsheets to 100 data analysts: the story of dbt at Slido From 100 spreadsheets to 100 data analysts: the story of dbt at Slido

From 100 spreadsheets to 100 data analysts: the story of dbt at Slido - Daniela Barokova, Michal Kolacek & Andrej Svec

To All The Data Managers We've Loved Before To All The Data Managers We've Loved Before

To All The Data Managers We've Loved Before - Paige Berry & Adam Stone

Stay Calm and Query on: Root Cause Analysis for Your Data Pipelines (Workshop Sponsor)

Stay Calm and Query on: Root Cause Analysis for Your Data Pipelines (Workshop Sponsor) - Francisco Alberini

Upskilling from an Insights Analyst to an Analytics Engineer

Upskilling from an Insights Analyst to an Analytics Engineer - Brittany Krauth

Modeling event data at scale (Workshop Sponsor)

Modeling event data at scale (Workshop Sponsor) - Will Warner

Building a metadata ecosystem with dbt

Building a metadata ecosystem with dbt - Darren Haken

New Data Role on the Block: Revenue Analytics

New Data Role on the Block: Revenue Analytics - Celina Wong

Using dbt to understand open-source communities

Using dbt to understand open-source communities - Srini Kadamati

Getting Meta about Metadata: Building Trustworthy Data Products Backed by dbt (Workshop Sponsor) Getting Meta about Metadata: Building Trustworthy Data Products Backed by dbt (Workshop Sponsor)

Getting Meta about Metadata: Building Trustworthy Data Products Backed by dbt (Workshop Sponsor) - Angie Brown & Kelechi Erondu

🍪 Eat the data you have: tracking core events in a cookieless world

🍪 Eat the data you have: tracking core events in a cookieless world - Jeff Sloan

Trials and Tribulations of Incremental Models

Trials and Tribulations of Incremental Models - Vincey Au

Sharing the knowledge - joining dbt and

Sharing the knowledge - joining dbt and "the Business" using Tāngata - Chris Jenkins

SQL Draw Artworks Review Panel

SQL Draw Artworks Review Panel - James Weakley

Tips for organizing inclusive digital events

The dbt community is filled with dedicated community leaders who create opportunities for connection, learning and professional development within the analytics community.

This guide is a resource to help organizers execute inclusive digital events. We understand that organizers, presenters, speakers, etc. might not be able to apply these tips to every event, but this guide will offer some food for thought.

If and when we return to in-person events, we will update this document to reflect how you can create an inclusive in-person event too.

Additionally, this list can grow. If you would like to contribute a tip, please email fatima@fishtownanalytics.com.

General logistics #

  • Try to choose a date that does not overlap with holidays or general major events. Don’t forget to check international holidays (if applicable)
  • Avoid really large national/local events (i.e. World Cup)

Marketing #

  • If you are using photos, share images that include community members from underrepresented groups
  • Put event accessibility information on your event page (i.e. “closed captioning available for all video resources”)
  • In the registration process provide an opportunity for attendees to:
    • share pronouns
    • ask questions in advance
    • request specific needs or other accommodations (interpreting services, braille transcription, dietary restrictions, etc.)
  • If this is a paid event (e.g. a conference), create a scholarship for attendees that might need financial support
  • Think about how you are promoting your event — are you reaching underrepresented communities, marginalized populations and people who might not have access to the internet?

Programming #

  • Book diverse speakers. Include speakers that represent underrepresented and marginalized populations.
  • Do research on your speakers. Is there any reason that your speakers would make the audience uncomfortable?
  • Design an accessible presentation
  • If possible, share a recording after the event for community members who are not able to make it and add closed captioning.
  • Ask speakers to introduce themselves before starting their presentation, so that transcription services can capture who is talking.

Platform #

  • Take a minute or two to explain the features of the platform that attendees will be using in the beginning of the event
  • Offer the option for attendees to dial-in by phone and participate without a computer or internet
  • Explore the accessibility features your platform offers and apply it where necessary (i.e. closed captioning, automatic transcripts, screen reader support, etc.)
  • Check if your platform is compatible with assistive technology

Attendee communication #

  • Make sure that attendees have any links, codes, numbers to accessing the event beforehand
  • Share the agenda of the event beforehand so that attendees are able to make arrangements (if necessary)
  • Share contact information with attendees so that they are able to reach out with questions before and after the event.
  • Ask attendees for feedback in a post-event survey so that you are able to improve future experiences.

Speaker communication #

  • Ask speakers how to pronounce their names before the event
  • Ask speakers for their pronouns before the event
  • Suggest that speakers use headphones to ensure clear audio
  • Ask speakers to use plain language and avoid jargon, slang, idioms, etc.