The health and safety of all Coalesce attendees is important to us. The on-site medical clinic will be staffed by paramedics offering on-site urgent care and a physician on-call via telehealth. COVID testing will also be available at the clinic. 

The health and safety of all Coalesce attendees is important to us. The on-site medical clinic will be staffed by paramedics offering on-site urgent care and a physician on-call via telehealth. COVID testing will also be available at the clinic.&nbsp;

San Diego

🩺 Medical clinic

The health and safety of all Coalesce attendees is important to us. The on-site medical clinic will be staffed by paramedics offering on-site urgent care and a physician on-call via telehealth. COVID...

Get certified at Coalesce! Choose from one of two certifications: dbt Developer and dbt Cloud Administrator. Your purchase includes sitting for one attempt for one of the two exams in person at Coalesce. Both exams are 2 hours in length, proctored in person, and you will need to bring your own computer to take the exam.

Get certified at Coalesce! Choose from one of two certifications: dbt Developer and dbt Cloud Administrator. Your purchase includes sitting for one attempt for one of the two exams in person at Coalesce. Both exams are 2 hours in length, proctored in person, and you will need to bring your own computer to take the exam.

Certification

Get certified at Coalesce! Choose from one of two certifications: dbt Developer and dbt Cloud Administrator. Your purchase includes sitting for one attempt for one of the two exams in person at...

Coalesce is the biggest gathering of the dbt Community world wide. As a dbt Labs partner, this is your exclusive opportunity to get an early view into the vision we have for dbt and learn how we can partner together to drive successful outcomes from our joint customers. Hear from Amy Deora, VP of Alliances, Tristan Handy, CEO and Co-Founder, and Luis Maldonado, VP of Product, as they share the state of dbt today, where we see it going tomorrow, and how we can partner together to win.

<span data-sheets-userformat='{"2":13187,"3":{"1":0},"4":{"1":2,"2":16776960},"10":2,"11":4,"12":0,"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"Coalesce is the biggest gathering of the dbt Community world wide. As a dbt Labs partner, this is your exclusive opportunity to get an early view into the vision we have for dbt and learn how we can partner together to drive successful outcomes from our joint customers. Hear from Amy Deora, VP of Alliances, Tristan Handy, CEO and Co-Founder, and Luis Maldonado, VP of Product, as they share the state of dbt today, where we see it going tomorrow, and how we can partner together to win."}'>Coalesce is the biggest gathering of the dbt Community world wide. As a dbt Labs partner, this is your exclusive opportunity to get an early view into the vision we have for dbt and learn how we can partner together to drive successful outcomes from our joint customers. Hear from Amy Deora, VP of Alliances, Tristan Handy, CEO and Co-Founder, and Luis Maldonado, VP of Product, as they share the state of dbt today, where we see it going tomorrow, and how we can partner together to win.

Partnerships

Product Manager

Partner Day: Welcome to Coalesce keynote

Partner day

Coalesce is the biggest gathering of the dbt Community world wide. As a dbt Labs partner, this is your exclusive opportunity to get an early view into the vision we have for dbt and learn how we can...

This is the introductory course for developers jumping into dbt! We will cover the same concepts from the on demand fundamentals course including models, sources, tests, docs, and deployment. We will also introduce the concepts of semantic layer and multi-project. As an instructor led course, you’ll have the chance to learn with peers, ask questions, and get live coaching and feedback. Learning objectives: After this course you will be able to: 

- Explain the core concepts of dbt 

- Build data models and a DAG to visualize dependencies 

- Configure tests and add documentation to your models 

- Deploy your dbt project to refresh data models on a schedule 

Prerequisites: The prerequisites for this course include: intermediate SQL knowledge 

What to bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt Cloud and data platform.

This is the introductory course for developers jumping into dbt! We will cover the same concepts from the on demand fundamentals course including models, sources, tests, docs, and deployment. We will also introduce the concepts of semantic layer and multi-project. As an instructor led course, you’ll have the chance to learn with peers, ask questions, and get live coaching and feedback. Learning objectives: After this course you will be able to:&nbsp;- Explain the core concepts of dbt&nbsp;- Build data models and a DAG to visualize dependencies&nbsp;- Configure tests and add documentation to your models&nbsp;- Deploy your dbt project to refresh data models on a schedule&nbsp;Prerequisites: The prerequisites for this course include: intermediate SQL knowledge&nbsp;What to bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt Cloud and data platform.

Training: Getting started with dbt

Training

This is the introductory course for developers jumping into dbt! We will cover the same concepts from the on demand fundamentals course including models, sources, tests, docs, and deployment. We will...

Want to learn more about the new capabilities in dbt Cloud? This session will provide demos and an opportunity ask questions about the new and exciting innovations being announced at Coalesce.

<span data-sheets-userformat='{"2":13187,"3":{"1":0},"4":{"1":2,"2":16776960},"10":2,"11":4,"12":0,"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"Want to learn more about the new capabilities in dbt Cloud? This session will provide demos and an opportunity ask questions about the new and exciting innovations being announced at Coalesce."}'>Want to learn more about the new capabilities in dbt Cloud? This session will provide demos and an opportunity ask questions about the new and exciting innovations being announced at Coalesce.

Partner Engineer Manager

Partner Engineer

Partner Day: Demo at first sight

As dbt Labs grows as a business, we are evolving our partner programs to optimize how we work together. Learn about the latest partner programs, and give us input that will help shape the programs we offer in the future.

<span data-sheets-userformat='{"2":13187,"3":{"1":0},"4":{"1":2,"2":16776960},"10":2,"11":4,"12":0,"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"As dbt Labs grows as a business, we are evolving our partner programs to optimize how we work together. Learn about the latest partner programs, and give us input that will help shape the programs we offer in the future."}'>As dbt Labs grows as a business, we are evolving our partner programs to optimize how we work together. Learn about the latest partner programs, and give us input that will help shape the programs we offer in the future.

Sr Partner Manager

Sr. Partner Manager

Partner Manager

Partner Day: Partnering with dbt Labs

As dbt Labs grows as a business, we are evolving our partner programs to optimize how we work together. Learn about the latest partner programs, and give us input that will help shape the programs we...

Bring your pressing questions for our select group of dbt Labs executives.

<span data-sheets-userformat='{"2":13187,"3":{"1":0},"4":{"1":2,"2":16776960},"10":2,"11":4,"12":0,"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"Bring your pressing questions for our select group of dbt Labs executives"}'>Bring your pressing questions for our select group of dbt Labs executives.

Vice President, Brand Marketing

Chief Revenue Officer

Partner Day: dbt Labs Executive Panel

Partners are central to our success. Let’s take a few moments to celebrate the ecosystem, and announce awards for our top performing partners across various categories.

<span data-sheets-userformat='{"2":13187,"3":{"1":0},"4":{"1":2,"2":16776960},"10":2,"11":4,"12":0,"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"Partners are central to our success. Let’s take a few moments to celebrate the ecosystem, and announce awards for our top performing partners across various categories."}'>Partners are central to our success. Let’s take a few moments to celebrate the ecosystem, and announce awards for our top performing partners across various categories.

Partner Day: dbt Labs partner awards

Join us for the Welcome Happy Hour on Monday, October 16th in the Activation Hall (Level 4) from 5:00 PM to 6:30 PM. It's your prime opportunity to connect with sponsors and mingle with fellow data enthusiasts!

Join us for the Welcome Happy Hour on Monday, October 16th in the Activation Hall (Level 4) from 5:00 PM to 6:30 PM. It's your prime opportunity to connect with sponsors and mingle with fellow data enthusiasts!

🎉 San Diego - Welcome happy hour

Join us for the Welcome Happy Hour on Monday, October 16th in the Activation Hall (Level 4) from 5:00 PM to 6:30 PM. It's your prime opportunity to connect with sponsors and mingle with fellow data...

Class: "Unwind" Slow Flow

Participants will be guided through a grounded breath work and a gentle seated and standing yoga sequence to allow the body to relax. This is a great option for those who are new to yoga.

Mats will be provided. 

Class: "Unwind" Slow FlowParticipants will be guided through a&nbsp;grounded breath work and a gentle seated&nbsp;and standing yoga sequence to allow the&nbsp;body to relax. This is a great option for those&nbsp;who are new to yoga.Mats will be provided.

🧘🏽 "Unwind" slow flow — brought to you by Census 

Class: "Unwind" Slow Flow

Participants will be guided through a grounded breath work and a gentle seated and standing yoga sequence to allow the body to relax. This is a great option for those who...

The health and safety of all Coalesce attendees is important to us. The on-site medical clinic will be staffed by paramedics offering on-site urgent care and a physician on-call via telehealth. COVID testing will also be available at the clinic.

The health and safety of all Coalesce attendees is important to us. The on-site medical clinic will be staffed by paramedics offering on-site urgent care and a physician on-call via telehealth. COVID testing will also be available at the clinic.

🩺  Medical clinic

Registration - Tuesday

🍽️  Breakfast

The Coalesce activation hall is not your typical conference expo floor. Each of our sponsors will have an interactive booth. At our inaugural event in 2022 attendees enjoyed tie-dye, a make-up station, origami, a diner, boba tea & more! There’s more exciting things planned from our sponsors this year!




Activation Hall schedule:

•Tuesday 8:00 AM to 5:00 PM
•Wednesday 8:00 AM to 5:00 PM
•Thursday 8:00 AM to 1:00 PM


The Coalesce activation hall is not your typical conference expo floor. Each of our sponsors will have an interactive booth. At our inaugural event in 2022 attendees enjoyed tie-dye, a make-up station, origami, a diner, boba tea &amp; more! There’s more exciting things planned from our sponsors this year! Activation Hall schedule:<ul><li>Tuesday 8:00 AM to 5:00 PM</li><li>Wednesday 8:00 AM to 5:00 PM</li><li>Thursday 8:00 AM to 1:00 PM</li></ul>

Activation Hall - Tuesday

The Coalesce activation hall is not your typical conference expo floor. Each of our sponsors will have an interactive booth. At our inaugural event in 2022 attendees enjoyed tie-dye, a make-up...

Kick off Coalesce at the Keynote and Product Spotlight!

Seven years ago, in the early days of dbt, dbt Labs was building capabilities that made data developers more productive. dbt gained traction. It took off. Today, dbt is the standard for data transformation. It has never been easier to build and ship data products. This has created a new challenge – complexity. Join Tristan Handy, Founder and CEO at dbt Labs, and Luis Maldonado, Vice President of Product at dbt Labs, to hear all about the latest releases in dbt and how they are helping organizations navigate complexity. Finally, you'll hear from data leaders at Fifth Third Bank on how they are implementing these new capabilities in dbt to execute on their data strategy and achieve better outcomes for the business.



Kick off Coalesce at the Keynote and Product Spotlight! Seven years ago, in the early days of dbt, dbt Labs was building capabilities that made data developers more productive. dbt gained traction. It took off. Today, dbt is the standard for data transformation. It has never been easier to build and ship data products. This has created a new challenge – complexity. Join Tristan Handy, Founder and CEO at dbt Labs, and Luis Maldonado, Vice President of Product at dbt Labs, to hear all about the latest releases in dbt and how they are helping organizations navigate complexity. Finally, you'll hear from data leaders at Fifth Third Bank on how they are implementing these new capabilities in dbt to execute on their data strategy and achieve better outcomes for the business.

Online

Vice President, Product

VP - Director of Product Ownership | Data Strategy

SVP  | Senior Director, Data Engineering

dbt Labs product spotlight & keynote

Keynote

Live streamed

Kick off Coalesce at the Keynote and Product Spotlight!

Seven years ago, in the early days of dbt, dbt Labs was building capabilities that made data developers more productive. dbt gained traction....

With the dbt Semantic Layer, you can define metrics alongside your dbt models, and access them from any integrated analytics tool. In this workshop, you’ll learn to set up your first metrics in dbt following best practices, getting them ready for downstream analysis.

With the dbt Semantic Layer, you can define metrics alongside your dbt models, and access them from any integrated analytics tool. In this workshop, you’ll learn to set up your first metrics in dbt following best practices, getting them ready for downstream analysis.

An introduction to the dbt Semantic Layer

Workshop

With the dbt Semantic Layer, you can define metrics alongside your dbt models, and access them from any integrated analytics tool. In this workshop, you’ll learn to set up your first metrics in dbt...

Amazon Redshift offers a scalable, high-performing data warehouse as-a-service to manage the growing volume and velocity of data that drives real-time decision making. Data teams running dbt Cloud on Amazon Redshift are able to deploy analytics code, following software engineering best practices such as modularity, continuous integration and continuous deployment (CI/CD), and embedded documentation. This eliminates the need to build and maintain complex data pipelines and reduces the operational burden and cost, so that you can focus on improving your downstream data applications. In this hands-on workshop, we'll show you how to build a scalable real-time analytics solution with Amazon Redshift and dbt Cloud. 

<span data-sheets-userformat='{"2":771,"3":{"1":0},"4":{"1":2,"2":16776960},"11":4,"12":0}' data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Amazon Redshift offers a scalable, high-performing data warehouse as-a-service to manage the growing volume and velocity of data that drives real-time decision making. Data teams running dbt Cloud on Amazon Redshift are able to deploy analytics code, following software engineering best practices such as modularity, continuous integration and continuous deployment (CI/CD), and embedded documentation. This eliminates the need to build and maintain complex data pipelines and reduces the operational burden and cost, so that you can focus on improving your downstream data applications. In this hands-on workshop, we'll show you how to build a scalable real-time analytics solution with Amazon Redshift and dbt Cloud. &quot;}">Amazon Redshift offers a scalable, high-performing data warehouse as-a-service to manage the growing volume and velocity of data that drives real-time decision making. Data teams running dbt Cloud on Amazon Redshift are able to deploy analytics code, following software engineering best practices such as modularity, continuous integration and continuous deployment (CI/CD), and embedded documentation. This eliminates the need to build and maintain complex data pipelines and reduces the operational burden and cost, so that you can focus on improving your downstream data applications. In this hands-on workshop, we'll show you how to build a scalable real-time analytics solution with Amazon Redshift and dbt Cloud.&nbsp;

Analyze petabytes of real-time data with Amazon Redshift and dbt Cloud

Amazon Redshift offers a scalable, high-performing data warehouse as-a-service to manage the growing volume and velocity of data that drives real-time decision making. Data teams running dbt Cloud on...

dbt has been adopted as an industry standard, now used by more than 25,000 organizations. For larger companies with more complex deployments, however, it can still be a challenge to sustain efficient collaboration around data development without sacrificing governance. Here is how dbt Cloud is helping to overcome that challenge.

dbt has been adopted as an industry standard, now used by more than 25,000 organizations. For larger companies with more complex deployments, however, it can still be a challenge to sustain efficient collaboration around data development without sacrificing governance. Here is how dbt Cloud is helping to overcome that challenge.

Scaling collaboration with dbt Cloud

Product tour

dbt has been adopted as an industry standard, now used by more than 25,000 organizations. For larger companies with more complex deployments, however, it can still be a challenge to sustain efficient...

A Financial Institution's success hinges on its ability to remain competitive in the digital space and the evolve its data culture. Fifth Third’s vision for data modernization isn’t just about adopting the latest technologies; it’s about enhancing the employee experience with data and promoting Data Product ownership. This breakout explores the Bank’s transition from legacy to modern data architecture, showcasing its realistic commitment to people, process and technology.

<span data-sheets-userformat='{"2":771,"3":{"1":0},"4":{"1":2,"2":16776960},"11":4,"12":0}' data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;A Financial Institution's success hinges on its ability to remain competitive in the digital space and the evolve its data culture. Fifth Third’s vision for data modernization isn’t just about adopting the latest technologies; it’s about enhancing the employee experience with data and promoting Data Product ownership. This breakout explores the Bank’s transition from legacy to modern data architecture, showcasing its realistic commitment to people, process and technology.&quot;}">A Financial Institution's success hinges on its ability to remain competitive in the digital space and the evolve its data culture. Fifth Third’s vision for data modernization isn’t just about adopting the latest technologies; it’s about enhancing the employee experience with data and promoting Data Product ownership. This breakout explores the Bank’s transition from legacy to modern data architecture, showcasing its realistic commitment to people, process and technology.

Banking on the future: Fifth Third’s real-world data modernization journey

Modernization & migration

A Financial Institution's success hinges on its ability to remain competitive in the digital space and the evolve its data culture. Fifth Third’s vision for data modernization isn’t just about...

In this session, the team at Rocket Money will explain how they built a Quote-to-Cash (Q2C) system in dbt Cloud that the accounting team uses for end-of-month close. This was also used to pass Rocket Money's first SOX audit with zero deficiencies. The presentation will review how the team gathered requirements (for different products, payment providers, etc.) and built and tested all of their models.

Staff Analytics Engineer

Quote-to-Cash: Automating accounting's end-of-month close process (and passing our first SOX audit)

Business critical data teams

In this session, the team at Rocket Money will explain how they built a Quote-to-Cash (Q2C) system in dbt Cloud that the accounting team uses for end-of-month close. This was also used to pass Rocket...

It’s 2023, why are software engineers still breaking analytics reporting? We’ve all been there, being alerted by an analyst or C-level stakeholders, saying “this report is broken”, only to spend hours determining that an engineer deleted a column on the source database that is now breaking your pipeline and reporting.
 
At Xometry, the data engineering team wanted to fix this problem at its root and give the engineering teams a clear and repeatable process that allowed them to be the owners of their own database data. Xometry named the process DPICT (data pipeline contract) and built several internal tools that integrated seamlessly with their developer’s microservice toolsets.
 
Their software engineers mostly build their database microservices using Postgres, and bring in the data using Fivetran. Using that as the baseline, the team created a set of tools that would allow the engineers to quickly build the staging layer of their database in the data warehouse (Snowflake), but also alert them of the consequences of removing a table or column in downstream reporting.


In this talk, Jisan will share with you the nuts and bolts of the designed solution and process that allowed the team to onboard 13 different microservices seamlessly, working with multiple domains and dozens of developers. The process also helped software engineers to own their own data and realize their impact. The team has saved hundreds hours of data engineering time and resources not having to chase down what changed upstream to break data. Overall, this process has helped to bring transparency to the whole data ecosystem.

<span data-sheets-userformat='{"2":15293,"3":{"1":0},"5":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"6":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"7":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"8":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"It’s 2023, why are software engineers still breaking analytics reporting? We’ve all been there, being alerted by an analyst or C-level stakeholders, saying “this report is broken”, only to spend hours determining that an engineer deleted a column on the source database that is now breaking your pipeline and reporting.\n \n\n At Xometry, we, the data engineering team, wanted to fix this problem at its core and wanted to give our engineering teams a clear and repeatable process that allowed them to be the owners of their own database data. We named our process DPICT (data pipeline contract) and built several internal tools that integrated seamlessly with our developer’s microservice toolsets.\n \n\n Our software engineers mostly build their database microservices using Postgres, and we bring in the data using Fivetran. Using that as our baseline, we created a set of tools that would allow the engineers to quickly build the staging layer of their database in our data warehouse (Snowflake) but also alert them of the consequences of removing a table or column in downstream reporting.\n \n\n In this talk, I will share with you the nuts and bolts of our designed solution and process that allowed us to onboard 13 different microservices seamlessly, working with multiple domains and dozens of developers. Our process also helped software engineers to own their own data and realize their impact. We’ve also saved hundreds hours of data engineering time and resources not having to chase down what changed upstream to break data. Overall, this process has helped to bring transparency to our whole data ecosystem."}'>It’s 2023, why are software engineers still breaking analytics reporting? We’ve all been there, being alerted by an analyst or C-level stakeholders, saying “this report is broken”, only to spend hours determining that an engineer deleted a column on the source database that is now breaking your pipeline and reporting. At Xometry, the data engineering team wanted to fix this problem at its root and give the engineering teams a clear and repeatable process that allowed them to be the owners of their own database data. Xometry named the process DPICT (data pipeline contract) and built several internal tools that integrated seamlessly with their developer’s microservice toolsets. Their software engineers mostly build their database microservices using Postgres, and bring in the data using Fivetran. Using that as the baseline, the team created a set of tools that would allow the engineers to quickly build the staging layer of their database in the data warehouse (Snowflake), but also alert them of the consequences of removing a table or column in downstream reporting. <span data-sheets-userformat='{"2":15293,"3":{"1":0},"5":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"6":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"7":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"8":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"It’s 2023, why are software engineers still breaking analytics reporting? We’ve all been there, being alerted by an analyst or C-level stakeholders, saying “this report is broken”, only to spend hours determining that an engineer deleted a column on the source database that is now breaking your pipeline and reporting.\n \n\n At Xometry, we, the data engineering team, wanted to fix this problem at its core and wanted to give our engineering teams a clear and repeatable process that allowed them to be the owners of their own database data. We named our process DPICT (data pipeline contract) and built several internal tools that integrated seamlessly with our developer’s microservice toolsets.\n \n\n Our software engineers mostly build their database microservices using Postgres, and we bring in the data using Fivetran. Using that as our baseline, we created a set of tools that would allow the engineers to quickly build the staging layer of their database in our data warehouse (Snowflake) but also alert them of the consequences of removing a table or column in downstream reporting.\n \n\n In this talk, I will share with you the nuts and bolts of our designed solution and process that allowed us to onboard 13 different microservices seamlessly, working with multiple domains and dozens of developers. Our process also helped software engineers to own their own data and realize their impact. We’ve also saved hundreds hours of data engineering time and resources not having to chase down what changed upstream to break data. Overall, this process has helped to bring transparency to our whole data ecosystem."}'>In this talk, Jisan will share with you the nuts and bolts of the designed solution and process that allowed the team to onboard 13 different microservices seamlessly, working with multiple domains and dozens of developers. The process also helped software engineers to own their own data and realize their impact. The team has saved hundreds hours of data engineering time and resources not having to chase down what changed upstream to break data. Overall, this process has helped to bring transparency to the whole data ecosystem.

Data Engineering Manager

Using data pipeline contract to prevent breakage in analytics reporting

On-demand

It’s 2023, why are software engineers still breaking analytics reporting? We’ve all been there, being alerted by an analyst or C-level stakeholders, saying “this report is broken”, only to spend...

As Joe Reis recently opined, if you want to know what’s next in data engineering, just look at the software engineer. The MDS-in-a-box pattern has been a game changer for applying software engineering principles to local data development– improving the ability to share data, collaborate on modeling work and data analysis the same way we build and share open source tooling.

This panel brings together experts in data engineering, data analytics and software engineering to explore the current state of the pattern, pieces that remain missing today and how emerging tools and data engineering testing capabilities can refine the transition from local development to production workflows.


<span data-sheets-userformat='{"2":9021,"3":{"1":0},"5":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"6":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"7":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"8":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"11":4,"12":0,"16":11}' data-sheets-value='{"1":2,"2":"Description\nAs Joe Reis recently opined, if you want to know what’s next in data engineering, just look at the software engineer. The MDS-in-a-box pattern has been a game changer for applying software engineering principles to local data development– improving the ability to share data, collaborate on modeling work and data analysis the same way we build and share open source tooling.\n\nThis panel brings together experts in data engineering, data analytics and software engineering to explore the current state of the pattern, pieces that remain missing today and how emerging tools and data engineering testing capabilities can refine the transition from local development to production workflows.\n\n"}'>As Joe Reis recently opined, if you want to know what’s next in data engineering, just look at the software engineer. The MDS-in-a-box pattern has been a game changer for applying software engineering principles to local data development– improving the ability to share data, collaborate on modeling work and data analysis the same way we build and share open source tooling. This panel brings together experts in data engineering, data analytics and software engineering to explore the current state of the pattern, pieces that remain missing today and how emerging tools and data engineering testing capabilities can refine the transition from local development to production workflows.

Developer Advocate

Solutions Engineer

Host

Panel discussion: Fixing the data eng lifecycle 

As Joe Reis recently opined, if you want to know what’s next in data engineering, just look at the software engineer. The MDS-in-a-box pattern has been a game changer for applying software...

TOCA Football, the largest Operator of Indoor Soccer Centers in North America, leverages accurate data to power analytics for over 30 training centers, providing everything from operational insights for executives to ball-by-ball analysis. 

In 2020, the team adopted a cloud-native data stack with dbt to scale analytics enablement for the go-to-market org, including the company’s finance, strategy, operations, and marketing teams. By 2022, their lean team of four was struggling to gain visibility into the health and performance of their dbt models. So, what was the TOCA team to do? Two words: data observability.
 
In this talk, Sam Cvetkovski, Director, Data & Analytics will discuss how TOCA built their larger data observability strategy to reduce model bloat, increase data accuracy, and boost stakeholder satisfaction with their team’s data products. She’ll share her biggest “aha!” moments, key challenges, and best practices for teams getting started on their dbt reliability journeys.

<span data-sheets-userformat='{"2":15293,"3":{"1":0},"5":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"6":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"7":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"8":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"TOCA Football, the largest Operator of Indoor Soccer Centers in North America, leverages accurate data to power analytics for over 30 training centers, providing everything from operational insights for executives to ball-by-ball analysis. In 2020, the team adopted a cloud-native data stack with dbt to scale analytics enablement for the go-to-market org, including the company’s finance, strategy, operations, and marketing teams. By 2022, their lean team of four was struggling to gain visibility into the health and performance of their dbt models. So, what was the TOCA team to do? Two words: data observability.\n \n\n In this talk, Sam Cvetkovski, Director, Data & Analytics will discuss how TOCA built their larger data observability strategy to reduce model bloat, increase data accuracy, and boost stakeholder satisfaction with their team’s data products. She’ll share her biggest “aha!” moments, key challenges, and best practices for teams getting started on their dbt reliability journeys."}'>TOCA Football, the largest Operator of Indoor Soccer Centers in North America, leverages accurate data to power analytics for over 30 training centers, providing everything from operational insights for executives to ball-by-ball analysis.&nbsp; <span data-sheets-userformat='{"2":15293,"3":{"1":0},"5":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"6":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"7":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"8":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"TOCA Football, the largest Operator of Indoor Soccer Centers in North America, leverages accurate data to power analytics for over 30 training centers, providing everything from operational insights for executives to ball-by-ball analysis. In 2020, the team adopted a cloud-native data stack with dbt to scale analytics enablement for the go-to-market org, including the company’s finance, strategy, operations, and marketing teams. By 2022, their lean team of four was struggling to gain visibility into the health and performance of their dbt models. So, what was the TOCA team to do? Two words: data observability.\n \n\n In this talk, Sam Cvetkovski, Director, Data & Analytics will discuss how TOCA built their larger data observability strategy to reduce model bloat, increase data accuracy, and boost stakeholder satisfaction with their team’s data products. She’ll share her biggest “aha!” moments, key challenges, and best practices for teams getting started on their dbt reliability journeys."}'>In 2020, the team adopted a cloud-native data stack with dbt to scale analytics enablement for the go-to-market org, including the company’s finance, strategy, operations, and marketing teams. By 2022, their lean team of four was struggling to gain visibility into the health and performance of their dbt models. So, what was the TOCA team to do? Two words: data observability. In this talk, Sam Cvetkovski, Director, Data &amp; Analytics will discuss how TOCA built their larger data observability strategy to reduce model bloat, increase data accuracy, and boost stakeholder satisfaction with their team’s data products. She’ll share her biggest “aha!” moments, key challenges, and best practices for teams getting started on their dbt reliability journeys.

Data is life: How TOCA football keeps their eye on the ball with dbt and data observability

dbt at scale

TOCA Football, the largest Operator of Indoor Soccer Centers in North America, leverages accurate data to power analytics for over 30 training centers, providing everything from operational insights...

🍽️ Lunch

New constructs in dbt make it simple to break up your monolothic dbt project into multiple smaller projects, with clear interfaces and robust governance. Learn to set up your own multi-project dbt deployment following best practices in this interactive workshop.

New constructs in dbt make it simple to break up your monolothic dbt project into multiple smaller projects, with clear interfaces and robust governance. Learn to set up your own multi-project dbt deployment following best practices in this interactive workshop.

Beyond the monolith: Multi-project approaches

New constructs in dbt make it simple to break up your monolothic dbt project into multiple smaller projects, with clear interfaces and robust governance. Learn to set up your own multi-project dbt...

In this “lean coffee” style session moderated by Jerrie and Phoenix, attendees will have the opportunity to control the flow of discussion in an agile format.

The overall topic, “Defining role boundaries” is one that comes up time and time again in data orgs. Session Facilitators Phoenix Jay & Jerrie Kumalah recently spoke together on this topic at another conference and now they are excited to co-host an in-person session to open the discussion to the Analytics Engineering community attending Coalesce 2023 in San Diego.

In-person attendees will have time to discuss and network around the common topic, and notes will be taken to track the discussion and collect the responses and themes.

In this “lean coffee” style session moderated by Jerrie and Phoenix, attendees will have the opportunity to control the flow of discussion in an agile format.The overall topic, “Defining role boundaries” is one that comes up time and time again in data orgs. Session Facilitators Phoenix Jay &amp; Jerrie Kumalah recently spoke together on this topic at another conference and now they are excited to co-host an in-person session to open the discussion to the Analytics Engineering community attending Coalesce 2023 in San Diego.In-person attendees will have time to discuss and network around the common topic, and notes will be taken to track the discussion and collect the responses and themes.

Analytics Engineer

Peer exchange: Defining role boundaries in big orgs

Peer exchange

In this “lean coffee” style session moderated by Jerrie and Phoenix, attendees will have the opportunity to control the flow of discussion in an agile format.

The overall topic, “Defining role...

Leveraging the power of RudderStack and dbt, Canadian Football League’s (CFL) data team abstracts the complexity of data in the warehouse and provides their marketing team with highly targeted audiences across a large variety of platforms and data sources. During this session we’ll hear how CFL went from manually sharing CSV files to modeling targeted segments, directly focused on OKRs, in their warehouse.

<span data-sheets-userformat='{"2":15233,"3":{"1":0},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":12}' data-sheets-value='{"1":2,"2":"Leveraging the power of RudderStack and dbt, Canadian Football League’s (CFL) data team abstracts the complexity of data in the warehouse and provides their marketing team with highly targeted audiences across a large variety of platforms and data sources. During this session we’ll hear how CFL went from manually sharing CSV files to modeling targeted segments, directly focused on OKRs, in their warehouse."}'>Leveraging the power of RudderStack and dbt, Canadian Football League’s (CFL) data team abstracts the complexity of data in the warehouse and provides their marketing team with highly targeted audiences across a large variety of platforms and data sources. During this session we’ll hear how CFL went from manually sharing CSV files to modeling targeted segments, directly focused on OKRs, in their warehouse.

Head of Product Marketing

Sr. Director, Business Intelligence 

How Canadian Football League’s data team runs winning marketing plays with dbt & RudderStack

Leveraging the power of RudderStack and dbt, Canadian Football League’s (CFL) data team abstracts the complexity of data in the warehouse and provides their marketing team with highly targeted...

In this session, we will highlight how dbt plays a key role in MuleSoft’s modern data analytics framework. As MuleSoft continues to grow, the data platform engineering team encountered some challenges with the data transformations. The session will dive deeper into the specific challenges faced by the team and demonstrate how dbt’s features including CI/CD, testing, documentation and lineage help overcome these challenges.

In this session, we will highlight how dbt plays a key role in MuleSoft’s modern data analytics framework. As MuleSoft continues to grow, the data platform engineering team encountered some challenges with the data transformations. The session will dive deeper into the specific challenges faced by the team and demonstrate how dbt’s features including CI/CD, testing, documentation and lineage help overcome these challenges.

Data Platform Engineer

Solution Architect

Powering the MuleSoft (a Salesforce Company) modern data analytics framework with dbt

In this session, we will highlight how dbt plays a key role in MuleSoft’s modern data analytics framework. As MuleSoft continues to grow, the data platform engineering team encountered some...

Hear from Red Ventures about how through the creation of standard implementation playbooks, their data team is able to quickly roll out modern tools like dbt and Hightouch across businesses to drive growth.

<span data-sheets-userformat='{"2":15235,"3":{"1":0},"4":{"1":2,"2":16776960},"10":0,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":12}' data-sheets-value='{"1":2,"2":"Hear from Red Ventures about how through the creation of standard implementation playbooks, their data team is able to quickly roll out modern tools like dbt and Hightouch across businesses to drive growth."}'>Hear from Red Ventures about how through the creation of standard implementation playbooks, their data team is able to quickly roll out modern tools like dbt and Hightouch across businesses to drive growth.

cofounder/co-CEO

Director of Data Engineering

Cost centers to cash cows: Data teams as growth drivers

Hear from Red Ventures about how through the creation of standard implementation playbooks, their data team is able to quickly roll out modern tools like dbt and Hightouch across businesses to drive...

With the dbt Semantic Layer, you can define metrics alongside your dbt models, and access them from any integrated analytics tool. 

The Semantic Layer has been totally revamped. It’s now powered by MetricFlow, allowing for more complex metric definition and a significantly improved querying experience. Join the dbt Labs product team as they dive into what’s new, what’s different, and what it means for you.

With the dbt Semantic Layer, you can define metrics alongside your dbt models, and access them from any integrated analytics tool. The Semantic Layer has been totally revamped. It’s now powered by MetricFlow, allowing for more complex metric definition and a significantly improved querying experience. Join the dbt Labs product team as they dive into what’s new, what’s different, and what it means for you.

Director, Product Management

The new-look dbt Semantic Layer, powered by MetricFlow

With the dbt Semantic Layer, you can define metrics alongside your dbt models, and access them from any integrated analytics tool. 

The Semantic Layer has been totally revamped. It’s now powered by...

In this session, Vida Health’s senior director of data, mobile, and web engineering will share a story that can help other data and business leaders capitalize on the opportunities being created by current technology innovations, market realities, and real-world problems. This includes a playbook on how Vida Health uses modern data technologies like dbt Cloud, Fivetran, Looker, BigQuery, BigQueryML/dbtML, Vertex AI, LLMs, and more to put data in the driver’s seat to solve meaningful problems in complex industries like healthcare.

In this session, Vida Health’s senior director of data, mobile, and web engineering will share a story that can help other data and business leaders capitalize on the opportunities being created by current technology innovations, market realities, and real-world problems. This includes a playbook on how Vida Health uses modern data technologies like dbt Cloud, Fivetran, Looker, BigQuery, BigQueryML/dbtML, Vertex AI, LLMs, and more to put data in the driver’s seat to solve meaningful problems in complex industries like healthcare.

Senior Director, Data and Frontend Engineering

Transforming healthcare by putting data in the driver’s seat at Vida Health

In this session, Vida Health’s senior director of data, mobile, and web engineering will share a story that can help other data and business leaders capitalize on the opportunities being created by...

This is the introductory course for developers jumping into dbt! We will cover the same concepts from the on demand fundamentals course including models, sources, tests, docs, and deployment. We will also introduce the concepts of semantic layer and multi-project. As an instructor led course, you’ll have the chance to learn with peers, ask questions, and get live coaching and feedback.
- learning objectives: After this course you will be able to:
    - Explain the core concepts of dbt
    - Build data models and a DAG to visualize dependencies
    - Configure tests and add documentation to your models
    - Deploy your dbt project to refresh data models on a schedule
- prerequisites: The prerequisites for this course include:
    - intermediate SQL knowledge
- what to bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt Cloud and data platform.

This is the introductory course for developers jumping into dbt! We will cover the same concepts from the on demand fundamentals course including models, sources, tests, docs, and deployment. We will also introduce the concepts of semantic layer and multi-project. As an instructor led course, you’ll have the chance to learn with peers, ask questions, and get live coaching and feedback. - learning objectives: After this course you will be able to: &nbsp; &nbsp;- Explain the core concepts of dbt &nbsp; &nbsp;- Build data models and a DAG to visualize dependencies &nbsp; &nbsp;- Configure tests and add documentation to your models &nbsp; &nbsp;- Deploy your dbt project to refresh data models on a schedule - prerequisites: The prerequisites for this course include: &nbsp; &nbsp;- intermediate SQL knowledge - what to bring: You will need to bring your own laptop to complete the hands-on exercises. We will provide all the other sandbox environments for dbt Cloud and data platform.

In this session, you'll learn tips and tricks from La-Z-Boy on how to modernize infrastructure and tackle complex retail and manufacturing data problems using dbt and Fivetran. Hear from a data leader about their experience and how you can replicate their success. Start your session off with some comfortable data movements to make sure you can extract as much information as possible from our loaded session on data transformation.

<span data-sheets-userformat='{"2":15293,"3":{"1":0},"5":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"6":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"7":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"8":{"1":[{"1":2,"2":0,"5":{"1":2,"2":0}},{"1":0,"2":0,"3":3},{"1":1,"2":0,"4":1}]},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":11}' data-sheets-value='{"1":2,"2":"Tips and tricks on how La-Z-Boy uses a modern data stack of Fivetran and dbt to modernize their infrastructure and tackle complex retail and manufacturing data problems. Hear from a data leader about their experience and how you can replicate their success. And start your session off with some comfortable data movements to make sure you can extract as much information as possible from our loaded session on data transformation."}'>In this session, you'll learn tips and tricks from La-Z-Boy on how to modernize infrastructure and tackle complex retail and manufacturing data problems using dbt and Fivetran. Hear from a data leader about their experience and how you can replicate their success. Start your session off with some comfortable data movements to make sure you can extract as much information as possible from our loaded session on data transformation.

Lead Product Marketing Manager

Director of Data Analytics & Enterprise Architecture

Move data comfortably: Modernizing your infrastructure with La-Z-Boy and Fivetran

In this session, you'll learn tips and tricks from La-Z-Boy on how to modernize infrastructure and tackle complex retail and manufacturing data problems using dbt and Fivetran. Hear from a data...

With dbt and the modern data stack, onboarding and surfacing data has never been more manageable for analytics engineers. Still, 85% of data products never make it into production. Why do data practitioners struggle to create data products that engage the people who actually use them?

Join Jake and Nate as they discuss how integration and collaboration can drive user engagement, ultimately leading to increased adoption. They’ll present guiding principles and three real world examples of data products designed to center and empower business users to:
- Replace the need for seeds using materialized Sigma input tables
- Create and manage HubSpot contacts and segments using Sigma’s HubSpot template
- Sync insights from Sigma directly to downstream systems using the Hightouch integration.

The lessons learned from building a data platform at Sigma will provide everyone a framework for fostering collaboration between data teams and business users so they can raid insights, move up the leaderboard, and level up their gameplay no matter what data stack they use.

<span data-sheets-userformat='{"2":961,"3":{"1":0},"9":0,"10":1,"11":4,"12":0}' data-sheets-value='{"1":2,"2":"With dbt and the modern data stack, onboarding and surfacing data has never been more manageable for analytics engineers. Still, 85% of data products never make it into production. Why do data practitioners struggle to create data products that engage the people who actually use them?\n\nJoin Jake and Nate as they discuss how integration and collaboration can drive user engagement, ultimately leading to increased adoption. They’ll present guiding principles and three real world examples of data products designed to center and empower business users to:\n- Replace the need for seeds using materialized Sigma input tables\n- Create and manage HubSpot contacts and segments using Sigma’s HubSpot template\n- Sync insights from Sigma directly to downstream systems using the Hightouch integration.\n\nThe lessons learned from building a data platform at Sigma will provide everyone a framework for fostering collaboration between data teams and business users so they can raid insights, move up the leaderboard, and level up their gameplay no matter what data stack they use."}'>With dbt and the modern data stack, onboarding and surfacing data has never been more manageable for analytics engineers. Still, 85% of data products never make it into production. Why do data practitioners struggle to create data products that engage the people who actually use them? Join Jake and Nate as they discuss how integration and collaboration can drive user engagement, ultimately leading to increased adoption. They’ll present guiding principles and three real world examples of data products designed to center and empower business users to: - Replace the need for seeds using materialized Sigma input tables - Create and manage HubSpot contacts and segments using Sigma’s HubSpot template - Sync insights from Sigma directly to downstream systems using the Hightouch integration. The lessons learned from building a data platform at Sigma will provide everyone a framework for fostering collaboration between data teams and business users so they can raid insights, move up the leaderboard, and level up their gameplay no matter what data stack they use.

Director of Partner Engineering, Sigma Computing

Senior Manager, Data Platform

Game on: Building massive multiplayer online data products

With dbt and the modern data stack, onboarding and surfacing data has never been more manageable for analytics engineers. Still, 85% of data products never make it into production. Why do data...

Prioritizing the right sales opportunities is pivotal for any SaaS company's growth, but what happens after your initial success? Join Jessica Zhang, Data Science Manager at Notion, as she traces Notion's footsteps from its foundational days, to its present-day lead scoring techniques. Learn how modern tools like dbt, Census, and Snowflake enable the Notion team to iterate quickly. More than a journey, this session is a lesson on evolving a data science model in response to changing business assumptions and fresh user insights.

<span data-sheets-userformat='{"2":15235,"3":{"1":0},"4":{"1":2,"2":16776960},"10":2,"11":4,"12":0,"14":{"1":2,"2":0},"15":"Calibri","16":12}' data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Prioritizing the right sales opportunities is pivotal for any SaaS company's growth, but what happens after your initial success? Join Jessica Zhang, Data Science Manager at Notion, as she traces Notion's footsteps from its foundational days, to its present-day lead scoring techniques. Learn how modern tools like dbt, Census, and Snowflake enable the Notion team to iterate quickly. More than a journey, this session is a lesson on evolving a data science model in response to changing business assumptions and fresh user insights.&quot;}">Prioritizing the right sales opportunities is pivotal for any SaaS company's growth, but what happens after your initial success? Join Jessica Zhang, Data Science Manager at Notion, as she traces Notion's footsteps from its foundational days, to its present-day lead scoring techniques. Learn how modern tools like dbt, Census, and Snowflake enable the Notion team to iterate quickly. More than a journey, this session is a lesson on evolving a data science model in response to changing business assumptions and fresh user insights.

Data Science Manager

Sr. Data Community Advocate

Navigating the scoring labyrinth: Notion’s blueprint for adapting data science models to changing sales processes

Prioritizing the right sales opportunities is pivotal for any SaaS company's growth, but what happens after your initial success? Join Jessica Zhang, Data Science Manager at Notion, as she traces...

Join the team from Moody's Analytics as they take you on a personal journey of optimizing their data pipelines for data quality and governance. Like many data practitioners, Ryan and Ravi understand the frustration and anxiety that comes with accidentally introducing bad code into production pipelines—they've spent countless hours putting out fires caused from these unexpected changes. 

In this session, Ryan and Ravi will recount their experiences with a previous data stack that lacked standardized testing methods and visibility into the impact of code changes on production data. They'll also share how their new data stack is safeguarded by Datafold's data diffing and continuous integration (CI) capabilities, which enables their team to work with greater confidence, peace of mind, and speed.

Join the team from Moody's Analytics as they take you on a personal journey of optimizing their data pipelines for data quality and governance. Like many data practitioners, Ryan and Ravi understand the frustration and anxiety that comes with accidentally introducing bad code into production pipelines—they've spent countless hours putting out fires caused from these unexpected changes. In this session, Ryan and Ravi will recount their experiences with a previous data stack that lacked standardized testing methods and visibility into the impact of code changes on production data. They'll also share how their new data stack is safeguarded by Datafold's data diffing and continuous integration (CI) capabilities, which enables their team to work with greater confidence, peace of mind, and speed.

Data Engineer

Identifying novel data issues that go undetected through CI/CD with dbt and Datafold

Join the team from Moody's Analytics as they take you on a personal journey of optimizing their data pipelines for data quality and governance. Like many data practitioners, Ryan and Ravi understand...

Continuous Integration (CI) in dbt Cloud makes it easy to test every change you make prior to deploying. It’s a hallmark of mature analytics workflows.We’ve made some major improvements to dbt Cloud CI, so it’s easier than ever to prevent breaking changes, save on costs, and keep those pesky stakeholders happy.

Join the dbt Labs product team on this magical journey to a world of better data quality, and see for yourself what CI can do for you.

Continuous Integration (CI) in dbt Cloud makes it easy to test every change you make prior to deploying. It’s a hallmark of mature analytics workflows.We’ve made some major improvements to dbt Cloud CI, so it’s easier than ever to prevent breaking changes, save on costs, and keep those pesky stakeholders happy.Join the dbt Labs product team on this magical journey to a world of better data quality, and see for yourself what CI can do for you.

Better CI for better data quality

Continuous Integration (CI) in dbt Cloud makes it easy to test every change you make prior to deploying. It’s a hallmark of mature analytics workflows.We’ve made some major improvements to dbt Cloud...

Fanduel, America's leading sports betting company, migrated all of its data pipelines to integrate with dbt Cloud in order to make data transformation processes more reliable, scalable, and maintainable.

In this presentation, the Fanduel team will share the challenges faced during the migration, including overcoming the inertia of established data infrastructure, integrating with legacy systems, and ensuring a smooth transition without disrupting ongoing data operations. The migration process fostered newfound collaboration among data analysts, product owners, and engineers, with the added benefit of accommodating future business needs.

<span data-sheets-formula="='San Diego - approved'!R[0]C[6]" data-sheets-userformat='{"2":256,"11":4}' data-sheets-value="{&quot;1&quot;:2,&quot;2&quot;:&quot;Fanduel, America's leading sports betting company, migrated all of its data pipelines to integrate with dbt Cloud in order to make data transformation processes more reliable, scalable, and maintainable.\n\nIn this presentation, the Fanduel team will share the challenges faced during the migration, including overcoming the inertia of established data infrastructure, integrating with legacy systems, and ensuring a smooth transition without disrupting ongoing data operations. The migration process fostered newfound collaboration among data analysts, product owners, and engineers, with the added benefit of accommodating future business needs.&quot;}">Fanduel, America's leading sports betting company, migrated all of its data pipelines to integrate with dbt Cloud in order to make data transformation processes more reliable, scalable, and maintainable. In this presentation, the Fanduel team will share the challenges faced during the migration, including overcoming the inertia of established data infrastructure, integrating with legacy systems, and ensuring a smooth transition without disrupting ongoing data operations. The migration process fostered newfound collaboration among data analysts, product owners, and engineers, with the added benefit of accommodating future business needs.

Technical Program Manager

Senior Data Engineer

How Fanduel migrated a mature data organization

Fanduel, America's leading sports betting company, migrated all of its data pipelines to integrate with dbt Cloud in order to make data transformation processes more reliable, scalable, and...

In this “lean coffee” style session moderated by Alexander, attendees will have the opportunity to control the flow of discussion in an agile format. In-person attendees will have time to discuss and network around the common topic, and notes will be taken to track the discussion and collect the responses and themes.

If you are a data analyst or engineer looking to expand your skillset, and if you want to learn new skills but feel overwhelmed by the vast amount of information out there, then this is the peer exchange session for you.

In this group, you can share share and learn practical strategies for mastering new skills from scratch, even if you have no prior experience in the field. As a group, we’ll discuss topics like how to identify the best resources for learning, how to stay motivated throughout the learning process, and how to apply what you’ve learned in real-world scenarios.

We may also explore specific examples of software engineering, data systems, and data architecture concepts, and provide tips for building a solid foundation in these areas. By the end of this peer exchange, you should have more tools and knowledge to more confidently tackle new skills.

In this “lean coffee” style session moderated by Alexander, attendees will have the opportunity to control the flow of discussion in an agile format. In-person attendees will have time to discuss and network around the common topic, and notes will be taken to track the discussion and collect the responses and themes. If you are a data analyst or engineer looking to expand your skillset, and if you want to learn new skills but feel overwhelmed by the vast amount of information out there, then this is the peer exchange session for you. In this group, you can share share and learn practical strategies for mastering new skills from scratch, even if you have no prior experience in the field. As a group, we’ll discuss topics like how to identify the best resources for learning, how to stay motivated throughout the learning process, and how to apply what you’ve learned in real-world scenarios. We may also explore specific examples of software engineering, data systems, and data architecture concepts, and provide tips for building a solid foundation in these areas. By the end of this peer exchange, you should have more tools and knowledge to more confidently tackle new skills.

Peer exchange: Strategies for skill acquisition

In this “lean coffee” style session moderated by Alexander, attendees will have the opportunity to control the flow of discussion in an agile format. In-person attendees will have time to discuss and...

This session is specifically designed for beginners and will guide you step-by-step to building your very first data source from scratch. You'll learn to navigate the new dbt Cloud IDE and gain a deep understanding of sources, source freshness, and tests. Discover the best practices of modern data management and set a strong foundation for your future projects.

This session is specifically designed for beginners and will guide you step-by-step to building your very first data source from scratch. You'll learn to navigate the new dbt Cloud IDE and gain a deep understanding of sources, source freshness, and tests. Discover the best practices of modern data management and set a strong foundation for your future projects.

Fresh foundations: Migrate a stored procedure into your first dbt model

This session is specifically designed for beginners and will guide you step-by-step to building your very first data source from scratch. You'll learn to navigate the new dbt Cloud IDE and gain a...

During the data team's short tenure (2.5 years) at ClickUp, they have built and scaled a fully modern data stack and implemented a warehouse-first data strategy. ClickUp's data is comprised of thousands of dbt models and upstream/downstream integrations with nearly every software at ClickUp. ClickUp use dbt Cloud and Snowflake to power dozens of downstream systems with audience creation, marketing optimization, predictive customer lifecycle ML, a PLG/PLS motion, and much more. This session will cover the foundational principles ClickUp follows and how warehouse-first thinking has unlocked tremendous value for ClickUp.

Head of Data

Warehouse-first data strategy at ClickUp

During the data team's short tenure (2.5 years) at ClickUp, they have built and scaled a fully modern data stack and implemented a warehouse-first data strategy. ClickUp's data is comprised of...

Highly technical data teams can easily expound the virtues of data mesh to their technical peers, but getting leaders and lesser technical colleagues can be a challenge. In this talk, Pardhu Gunnam, CEO of Metaphor Data, will talk about the steps to sell the vision and build consensus across the organization for a successful implementation of data mesh.

Highly technical data teams can easily expound the virtues of data mesh to their technical peers, but getting leaders and lesser technical colleagues can be a challenge. In this talk, Pardhu Gunnam, CEO of Metaphor Data, will talk about the steps to sell the vision and build consensus across the organization for a successful implementation of data mesh.

5 steps to data mesh nirvana

Highly technical data teams can easily expound the virtues of data mesh to their technical peers, but getting leaders and lesser technical colleagues can be a challenge. In this talk, Pardhu Gunnam,...

Salesforce’s data-centric culture and sheer scale make adopting best practices in data a necessity. Over the last year, more and more teams within Salesforce have chosen to adopt dbt Cloud as a governed solution to centralize their business logic. This is the story of that adoption journey, the challenges that data teams in Salesforce have overcome, and what lies ahead. 

Salesforce’s data-centric culture and sheer scale make adopting best practices in data a necessity. Over the last year, more and more teams within Salesforce have chosen to adopt dbt Cloud as a governed solution to centralize their business logic. This is the story of that adoption journey, the challenges that data teams in Salesforce have overcome, and what lies ahead.&nbsp;

Salesforce & dbt Cloud: Charting new horizons in data collaboration

Salesforce’s data-centric culture and sheer scale make adopting best practices in data a necessity. Over the last year, more and more teams within Salesforce have chosen to adopt dbt Cloud as a...

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