dbt adoption has exploded—often before users had the resources and best practices at their disposal to inform strong project structure. But all is not lost! With the collective experience of 6 dbt-using data teams under their belt, Kelly Burdine and Michelle Ballen know exactly how to take your project from worst to first.

Check the slides here: https://docs.google.com/presentation/d/1P9kY0a9UAwp1Z3YrQGqhkn6hn4npKcf9lwDV1KNZ7tU/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

How do you support exponentially growing companies without breaking as a data team? The answer is increasing your leverage with tools and processes. This session centers around four principles to achieve this goal: 1. don’t reinvent the wheel, 2. make your own job easier, 3. save time for innovation, and 4. invest in onboarding.

First, the first data leader at Vendr, the SaaS buying platform with customers like GitLab, Brex, and The Washington Post, will share his learnings on building a stack and team that scaled as the company grew 10x from 30 to 300 employees in under two years.

Second, we’ll give a demo of how Metaplane pulls lineage and metadata from a modern data stack that is centered around dbt. By the end of the demo, you’ll know how to setup tests, extract lineage throughout your data stack, and triage data quality alerts.More details coming soon!

Check the slides here: https://docs.google.com/presentation/d/15dQJIGeGhG0WGO6MLXtxWhmf8neY-u0c8ZLRG9GJB-s/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Roleplaying games? Roleplaying games in data? You read that right. To Ian, there's more commonality in roleplaying games and the data world than most of us think. In this session, Ian Fahey (dbt Labs) will draw on his vast experiences in roleplaying games and analytics engineering work to walk through the adventuring classes of "the world's most popular tabletop roleplaying game" (Dungeons and Dragons) and talk about how they can inform data professionalism.

Check the slides here:https://docs.google.com/presentation/d/16Wm4ChDPORvEkDxUu3-mHBYRLJtwUTRdP7rj-LIrUB4/edit#slide=id.g1571952a68b_0_12

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

For too long, there's been contention between business and data teams. Incoming requests to a data team span from adding one specific column for one specific use case, to updating logic for a point in time question—the priorities stack up, and data teams find themselves sifting through a myriad of lower-level requests, unable to work on higher, more transformational deliverables. At Sigma, we're flipping the script by enabling analysts and stakeholders alike to iterate and explore in a familiar spreadsheet UI, with the scale and performance unlocked by modern cloud data warehouses. In this talk, we'll cover how we deploy Sigma internally (powered by dbt and dbt cloud metadata) to truly give the power to generate insights from data back to the business, and create a more effective feedback loop when working with our own data team.

Check the slides here: https://docs.google.com/presentation/d/11jGG6OSwwjtT6gRVpse9VSPjW_mIpYPUfRBx5TSttjk/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

For the first time in dbt, you can now run Python models, making it possible to supplement the accessibility of SQL with a new level of power and flexibility.

When is it useful to use Python, and when should you stick with SQL instead? What might a multilingual dbt project look like in practice, and what could it make possible for your team?

Join Jeremy Cohen, Cody Peterson, and Leah Antkiewicz to explore these questions in this interactive session.

Check the slides here: https://docs.google.com/presentation/d/1e3wB7EQ0EXugGhfCjVCp_dDFEbY_uKyVjMqG1o7alnA/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Does a two-step deployment workflow for developing, testing, and deploying code to dbt Cloud sound possible? Sunrun thinks so. Join James Sorensen and Jared Stout to learn how they used Github Actions and API integrations with dbt Cloud and Jira to entirely automate the CI/CD workflow, saving the team time and worry when moving through SOX certification.

Check the slides here: https://docs.google.com/presentation/d/1ZecU0-TN8SxNFpdKdkVksuDjpUy6XiaulqBdfqhLb68/edit#slide=id.g15507761f0b_0_10

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Automation will make your dbt development faster and safer — but how do you get started? In this workshop we'll introduce you to the "Software Development Life Cycle" and some of the automation opportunities it offers from pre-commit to CI and beyond.

This workshop is ideal for the decision maker who is planning for their team or for the intermediate to advanced dbt developer who wants to become more efficient and learn a thing or two from software workflows. We'll talk about how automation can minimize the risk of code changes, shorten your time to merge, and improve quality and standardization throughout your projects.

Bring your laptop with dbt 1.0+ installed to follow along or just come and watch the walk-through! You'll start this workshop with a simple dbt project and end with local pre-commit automation on your computer and a framework for further improvement and iteration.

Check the step-by-step workshop guide here: https://blog.montrealanalytics.com/automating-dbt-development-workflows-with-pre-commit-b6c7ca708f7

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Supplying users with the most relevant data is a time-consuming challenge. By combining the power of dbt with machine learning (ML) analysis, companies are able to focus on the most relevant segments in the data that have the greatest impact on key metrics and how they change over time. Leveraging the Sisu Decision Intelligence Engine, dbt users, analysts, and data scientists focus their efforts where they have the greatest impact. Sisu's AI/ML-powered automated analytics identifies relevant data and predicts changes, helping focus data exploration, speed insights, and drive successful outcomes.

Check Notion document here: https://www.notion.so/6382db82046f41599e9ec39afb035bdb

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Let’s get down to business! Most business users don't want to be bogged down in the data modeling and complexities that us data folk work so hard to accomplish and overcome. Instead, business users and leadership members want the dashboards and numbers they care about. In this session, Matthew Hoss (Element Biosciences) shares his four-step approach to modeling and creating turnkey cost dashboards, all sitting on top of a Netsuite/Fivetran/Snowflake/dbt/Tableau data stack, that help business users get the answers they need, quickly.

Check the slides here: https://docs.google.com/presentation/d/1VVZwm2Kloy1aeewqbB--7WfxIifnpIZflx9V8Q2N-x0/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Many transformations are fine candidates for concretizing with dbt. But there are transformations that live in the data science world that are not well-suited for dbt—and probably for good reason. Consider the total set of all transformations, from mandatory pre-processing steps to sophisticated statistical transformations (e.g., converting data types versus computing robust measures of central tendency). The question quickly becomes: How do data teams decide which transformations to push down to dbt and which to leave up in the notebook?

In this panel discussion led by Allan Campopiano (Deepnote), analytics engineers, data engineers, and data scientists discuss what transformation means to them, where and when transformation happens in their stack, and how to collaborate effectively between high- and low-level forms of transformation.

Check the slides here: https://docs.google.com/presentation/d/1uqi1C2gpBnsMp-BTvjltmjlnedWKqEzwonZjrewOWNk/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Academia/open science is an as-yet untapped market for analytics engineering, as well as one that could majorly benefit from the tight coupling of data transformation and software engineering best practices. But introducing dbt into this context comes with its own set of challenges. In this session, Šimon Podhajský (iLife Technologies), explains what’s slowing progress here,, and what academics can do to progress this work.

Check the slides here: https://docs.google.com/presentation/d/1aw_cs6V0n-oT9Lp7Vq3MNcRbthEFJEYwcvkCBfuzlR0/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Are you sold on dbt, but unsure as to how you’ll handle deployment, orchestration and job scheduling? Are you evaluating dbt and looking for an easy way to spin up a proof of concept while seeking buy in from stakeholders? Look no further! In this workshop we will show you how to containerize your dbt project and execute jobs using GCP’s serverless computing products Cloud Run, Build and Scheduler. If you have an interest in dbt orchestration, devops, or serverless cloud architecture, this workshop is for you!

Check the slides here: https://docs.google.com/presentation/d/1NiG0MFkOvw5MNpCZFF74VDuX-jHZpO4a8bHUadukoPI/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

As data science and machine learning adoption grew over the last few years, Python moved up the ranks catching up to SQL in popularity in the world of data processing. SQL and Python are both powerful on their own, but their value in modern analytics is highest when they work together. This was a key motivator for us at Snowflake to build Snowpark for Python: to help modern analytics, data engineering, and data science teams generate insights without complex infrastructure management for separate languages.

Join this session to learn more about how dbt's new support for Python-based models and Snowpark for Python can help polyglot data teams get more value from their data through secure, efficient and performant metrics stores, feature stores, or data factories in the Data Cloud.

Check Notion document here: https://www.notion.so/6382db82046f41599e9ec39afb035bdb

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Building data pipelines is difficult—and adding a data governance and observability framework doesn’t make it any easier. But that was the task ahead for Deepak Konidena during his early days at Zillow. In this session, he’ll share how the platform they build on top of dbt, Airflow, Spark, and Kubernetes—ZSQL—eliminated the need for internal data teams to build their own DAGs, models, schemas and lineage from scratch, while also providing an easy way to enforce data quality, monitor changes, and alert on disruptions.

Check the slides here: https://docs.google.com/presentation/d/18HEil3_nXD8nYBhcg4m-Kpy8I8Na6MXI/edit?usp=sharing&ouid=110293204340061069659&rtpof=true&sd=true

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Pulling data directly out of application databases is commonplace in the MDS, but also risky. Apps change quickly, and application teams might update database schemas in unexpected ways, leading to pipeline failures, data quality issues, data delivery slow-downs. There is a better way. In his session, Charlie Summers (Merit) describes how their organization transforms application event streams into analytics-ready tables, more resilient to event scheme changes.

Check the slides here:https://docs.google.com/presentation/d/1K5PcoVshiHKZs_xI3K4P5JRNYTkbmnQJPMl8NmBlGfo/edit

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Let's face it, we can't get enough data these days and often ingest from various sources like vendors, IoT devices, and more. Unfortunately, you've likely encountered times when the data just isn't what you're expecting. For instance; when the data has nulls, duplicates, is arranged differently than the schema specification, or others - this can be a weak point for many data pipelines. We'll showcase a way to handle this using dbt native methods to implement an inspection layer to ensure erroneous data sets can be flagged and quarantined while the rest can load uninterrupted.

Check the slides here: https://docs.google.com/presentation/d/11Q9wwMfyz6xuxMXCPizFg4DKSY_zOIHPNOrsNI8oBn8/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

See how visual data modeling and dbt combine to improve interaction and understanding between analytics engineering practitioners, product owners, and business partners. We will demonstrate conceptual and logical modeling techniques and diagrams to establish common understanding, enhance business partner collaboration, enhance translation of requirements, and ultimately complement analytics engineering within dbt to improve time to value. Demonstrate how to pair data modeling concepts (conceptual, logical, physical) and tools (SqlDBM) to engage your customers and inform the analytics engineering with dbt and Snowflake. We will show how this workbench and tools complement the analytics lifecycle for engineers and data consumers alike. The workbench includes a dbt, a visual modeling tool, and phData Toolkit CLI.

This session requires pre-registration. Sign up here. If session is filled you are welcome to come to the room and join the waitlist onsite. Open seats will be made available 10 minutes after session start.

Check the slides here: https://docs.google.com/presentation/d/1fJhaMGvD7TvVft4nEJYhMRhyanQTw3lbzLrgZFsmj-0/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

The long-awaited dbt Semantic Layer is finally here. By defining metrics centrally in dbt, data teams can trust that business logic referenced anywhere will be exactly the same everywhere. Experience it in action in this hands-on session with the dbt Labs product team and dbt Labs partners.

Check the slides here: https://docs.google.com/presentation/d/1lOH6Sb8DQnnlmZkYOlqqHgQeXKkUEQCm_LOxsjBRJlM/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

When the content analytics team at Spotify adopted dbt and shifted away from an internally developed transformation tool, they needed to figure out how to access data produced by other teams using sharded partitions. Enter: Waluigi. Nick Baker, Brian Pei, and Mitchell Silverman show us how an internal package used to safely and smoothly ingest the data they need also helped empower other data teams to more easily adopt dbt and leverage the data they produce.

Check the slides here: https://docs.google.com/presentation/d/1uAzfKa2Usbbr7J6jcI-IwdK1gPTKEsWSgZEfTU5bulM/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

For enterprises integrating dbt into their transformation technology stack, of paramount importance is how to achieve speed and scale. Sure, dbt will "infinitely scale" due to its underlying cloud native deployment- but only in reference to hosting, execution, and other platform services. HOW does one onboard hundreds or thousands of users with repeatability, conformity, and engineering excellence by design? HOW does an organization integrate dependent platforms and services? Centrally monitor? Share reusable assets? Maintain security?... This talk identifies how Cisco enabled automated services and processes to achieve that scale. Walk away knowing what's in store for you if onboarding dbt, headwinds we faced, and the success Cisco is seeing in our chosen deployment paradigm.

Check the slides here: https://docs.google.com/presentation/d/1e4fG0_60APnCmFDV5a8X7sPOCbKlto3L/edit?usp=sharing&ouid=110293204340061069659&rtpof=true&sd=true

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.