My first in-person whole-week conference — Coalesce 2022

6 min readOct 22, 2022

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😅 I’m not alone!

This is my biggest takeaway from dbtCoalesce 2022. “Revenue”! Data people understand. We have all been there. “Single source of truth,” “Collaboration with others.” It’s easy to say. Many speakers talk about the same struggles. Identifying the problems are already grateful to me. They provide solutions. 🤩

What I attend

Many sessions compete with each other at the same time. I already filtered by adding interesting sessions on my calendar. Still, there are many I miss.

Below I put on what I learned most from the session instead of the note. I’m a product manager builds company-wide data literacy and empowers the product team to create value for people and grow the company to profit. So you know my focus.

I don’t want to provide 2nd hand information. You should watch the sessions yourself. You may have different learnings!

You can find all sessions here and see the video after registration.
dbt Lab uploads all recordings to their YouTube.
Shared community note for Coalesce 2022

The missing link: Design as a daily activity

Introduction of this session

She identifies 3 activities. For each thing, we can look into these 3 activities to decide what skills so what people can handle it, e.g. 1 person can do it, or it should be done by Sr. Analytics engineer + product manager.

This is very helpful to me. I came to the conference to talk about data team should “sit together” with other teams. But I don’t know how. 🤪

All aboard! Why cross-team buy-in is the key to smooth sailing

Introduction of this session

Set myself to success. Like traveling, I get well-prepared to enter a place I have never been. Partnering with other teams is the same. I should speak their language and talk in a way they can understand.

The most helpful reminder is to respect others. I’m not here to show some advanced or modern way. I’m here to help others succeed. And success is defined by them.

Following up, I find these articles helpful.

A Culture of Partnership — Locally Optimistic
The Data Business Partnership — Locally Optimistic introduced by Data-led is dumb.

Data-led is dumb

Introduction of this session

You see the evolution from her talks in 3 Coalesce.

2020, run your data team as a product team
2021, Down with “data science”. Breaking Your Data Team out of the Service Trap
2022, Data-led is Dumb

We look for the outcome, not the output.

Money, Python, and the Holy Grail: Designing Operational Data Models

Introduction of this session

Data team should think about how we model our business in the way economist thinks about economics.

This talk explains the operation more clearly. Not a lot of metrics, but how they work together. I like the simplicity. Surprisingly, this is what a product team is looking for.

Following up, another attendee I met later on lunch suggested Why Every Data Team Needs a “Money Tree.” It’s amazing to see the similar concept from data and product! (Another core! 🤩) OST, opportunity solution tree, developed by Teresa Torres. She talks about the product team should find the product outcome, the leading metric, to support the business outcome, the lagging one.

Keynote: The End of the Road for The Modern Data Stack You Know

YouTube video of this keynote

We want to have shared knowledge. Shared so we can collaborate toward better outcomes. It’s more physical to transfer what we learned into (SQL) code. dbt Lab’s mission is “Empower data partitioners to create and disseminate organizational knowledge.”

Follow up readings, go to The Knowledge-Creating Company.

dbt Lab knows my day-to-day problem. They recognized it simply and are working on it already!

Of course, there are exciting announcements: Python model and Semantic layer. (Check out how Jeremy walked through dbt Python + Databricks at 1:12:00 👍)

Do analytics teams need product managers?

Introduction of this session

Her answer is no in the early stage or small company. I agree. ✅ (I'm a product manager 😆.)

She raises this question so people can discuss it. As a PM, I want to create value. If analytics engineers can do the (data) prodcut discovery, and they already do (data) product delivery, I'm more than happy to see.

From Data Magician to Data Coach

Introduction of this session

I love her slides. So cute. 💕 She calls outs accountability, getting into impact. We all want to get there.

Others sessions I went

And there are many I want to check out later online.

Sharing is important though the conversion is the best 😍

Each sharing has a slack channel. You can see the thought spreading from the speaker to the audience. Then you can participate at any time. (➡️ Join dbt community)

At every meal, actually, at any time, I can start a conversation with people around me. Amazingly, I ran into people who have related interests or experience. (Not just data!) I met product managers, people who worked for big companies and then go to startups, 1st-time or experienced managers…etc. It’s like fish in the water. 🐠

Not the same opinion. People give me new information, things I have never thought about, and tools I have never heard of. Challenge or confirm what I already concluded.

Extend my supporting system

I learn things from comparing notes. Though I am already in dbt community, sometimes chat with people on slack. The in-person conversion builds a closer connection. Maybe also because people showed up here commit their time already. Everyone is friendly and open to sharing.

Shout out to dbt Labs 💜💜

I’m glad I decided to come. Meeting you in person is wonderful. Thanks for all the arrangements, great good, details. I feel welcome and comfortable 🥰 here.