Behind any good DataOps within a Modern Data Stack (MDS) architecture is a solid DevOps design! This is particularly pressing when building an MDS solution at scale, as reliability, quality and availability of data requires a very high degree of process automation while remaining fast, agile and resilient to change when addressing business needs.

While DevOps in Data Engineering is nothing new - for a broad-spectrum solution that includes data warehouse, BI, etc seemed either a bit out of reach due to overall complexity and cost - or simply overlooked due to perceived issues around scaling often attributed to the challenges of automation in CI/CD processes. However, this has been fast changing with tools such as dbt having super cool features which allow a very high degree of autonomy in the CI/CD processes with relative ease, with flexible and cutting edge features around pre-commits, Slim CI, etc.

In this session, Datatonic covers the challenges around building and deploying enterprise-grade MDS solutions for analytics at scale and how they have used dbt to address those - especially around near-complete autonomy to the CI/CD processes!

Speaker: Ash Sultan, Lead Data Architect, Datatonic

Register for Coalesce at https://coalesce.getdbt.com

There’s a lot of decisions that need to be made throughout the initial deployment, migration to and scaling of the data stack. The decisions can be big or small, hard to reverse or trivial. When looking back at Zip’s modernization journey, there’s some things that the team nailed and others that they’d definitely do differently if they were to do it again. In this talk, the Zip team goes through the principles they used to make decisions when building out their stack, the challenges that they faced, the solutions that they landed on, and their learnings.

Speaker: Moss Pauly, Senior Manager Data Products, Zip

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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.

Speakers: Matt Housley, CTO, Halfpipe Systems; Mehdi Ouazza, Developer Advocate, MotherDuck; Sung Won Chung, Solutions Engineer, Datafold; Louise de Leyritz, Host, The Data Couch podcast

Register for Coalesce at https://coalesce.getdbt.com

Learn about Watercare's journey in implementing a modern data stack with a focus on self serving analytics in the water industry. The session covers the reasons behind Watercare's decision to implement a modern data stack, the problem of data conformity, and the tools they used to accelerate their data modeling process. Diego also discusses the benefits of using dbt, Snowflake, and Azure DevOps in data modeling. There is also a parallel drawn between analytics and Diego’s connection with jazz music.

Speaker: Diego Morales, Civil Industrial Engineer, Watercare

Register for Coalesce at https://coalesce.getdbt.com

In this presentation, Sarah and Darren discuss RMIT University's journey to implementing the modern data stack with dbt. They bring tales of their musical successes and misadventures, lessons learned with both music and data engineering, and how these seemingly disparate worlds overlap.

Speakers: Darren Ware, Senior Data Engineer, RMIT University; Sarah Taylor, Lead Data Engineer, RMIT University

Register for Coalesce at https://coalesce.getdbt.com

Florence is in the business of healthcare staffing. It is an incredibly outdated industry but with the help of the modern data stack, Florence has been able to make people's lives easier. Here is an overview on the challenges and tactics on how the team at Florence overcame them.

Speakers: Monica Youn, Chief Analytics Officer, Florence; Daniel Ferguson, Data Engineer, Florence

Register for Coalesce at https://coalesce.getdbt.com

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.

Speakers: Nate Meinzer, Director of Partner Engineering, Sigma Computing; Jake Hannan, Senior Manager, Data Platform, Sigma Computing

Register for Coalesce at https://coalesce.getdbt.com

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 uses 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 covers the foundational principles ClickUp follows and how warehouse-first thinking has unlocked tremendous value for ClickUp.

Speakers: Marc Stone, Head of Data, ClickUp

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In this session, gain strategic guidance on how to deploy dbt Cloud seamlessly to a team of 5-85 people. You'll learn best practices across development and automation that will ensure stability and high standards as you scale the number of developers using dbt Cloud and the number of models built up to the low thousands.

This session is a great fit for folks with beginner through intermediate levels of experience with dbt. In basketball terms, this talk covers mid-range shooting skills, but does not go into detail about 3-pointers, let alone half court shots. Likewise, this talk is not for people who are brand new to dbt and aren't familiar with the basic architecture of dbt and the modern data stack.

Speakers: Chris Davis, Senior Staff Engineer, Udemy, Inc.

Register for Coalesce at https://coalesce.getdbt.com

This panel discussion led by Data Clymer brings together data leaders from some of the top professional sports organizations in the U.S. to explore how sports and similar mid-size businesses are leveraging data and analytics engineering best practices to fuel revenue growth, improve business efficiencies, and drive fan engagement.

Speakers: Jesse McCabe, Vice President Marketing, Data Clymer; Keelan Smithers, Data Product Manager, Analytics Engineering, NBA; Paimon Jaberi, Managing Director of Strategy and Analytics, Seattle Seahawks; Jared Chavez, Senior Data Engineer, Pacers Sports & Entertainment

Register for Coalesce at https://coalesce.getdbt.com

When a startup is in its early stages, the data infrastructure is typically built with the best intentions, but doesn’t necessarily scale, and often predates many modern data tools available today. Years later, you might find yourself juggling complexity and tech debt when providing insights. This talk shares the journey Unbounce embarked on to modernize their data stack, including approaches to the following hurdles: demonstrating value and ROI to leadership for buy-in; deciding which tools to adopt; coordinating with data engineers and data analysts to deliver the cross-team project; and ensuring there were no interruptions to stakeholders throughout the migration.

Speaker: Morgan Cabot, Analytics engineering technical lead, Unbounce

Register for Coalesce at https://coalesce.getdbt.com

In this session, you'll learn about Rebtel's migration journey from a legacy architecture to the modern data stack. Due to the challenges of Rebtel's stack, the data product value was decreasing in the company, it was time to migrate. Learn how the team is using dbt Cloud and Snowflake to achieve greater success in delivering value to the business. You'll leave with a richer understanding of how to plan and execute a legacy migration.

Speaker: Quentin Coviaux, Data Engineer, Rebtel

Register for Coalesce at https://coalesce.getdbt.com

Lauren Benezra has been volunteering with a local cat rescue since 2018. She recently took on the challenge of rebuilding their data stack from scratch, replacing a Jenga tower of incomprehensible Google Sheets with a more reliable system backed by the Modern Data Stack. By using Airtable, Airbyte, BigQuery, dbt Cloud and Census, her role as Foster Coordinator has transformed: instead of digging for buried information while wrangling cats, she now serves up accurate data with ease while... well... wrangling cats.

Viewers will learn that it's possible to run an extremely scalable and reliable stack on a shoestring budget, and will come away with actionable steps to put Lauren's hard-won lessons into practice in their own volunteering projects or as the first data hire in a tiny startup.

Speakers: Lauren Benezra, Senior Analytics Engineer, dbt Labs

Register for Coalesce at https://coalesce.getdbt.com/