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/.

The opportunities for AI and machine learning are everywhere in modern businesses, but today's MLOps ecosystem is drowning in complexity. In this talk, we'll show how to use dbt and Continual to scale operational AI — from customer churn predictions to inventory forecasts — without complex engineering or operational burden.

Check the slides here: https://docs.google.com/presentation/d/1vNcQxCjAK4xZVZC1ZHzqBzPiJE7uwhDIVWGeT9Poi1U/edit#slide=id.g15b1f544dd5_0_1500

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

In between JVM languages, high-maintenance frameworks and academic papers, streaming remains a hard beast to tame for most of us. What if nothing had to change, and streaming just meant…still writing dbt models? At Materialize, we’re exploring how to make the most of dbt for streaming — from real-time analytics to continuous testing, and beyond! Join us to learn how to get started with no blood, sweat or tears, using the Jaffle Shop as a playground. Our toolbox? A database that feels like Postgres but works like all the streaming systems you’ve been avoiding, some SQL and a dash of magic.

Check the slides here: https://docs.google.com/presentation/d/11PANQElVxtzqgzmRCcQfZy24vdMeYDokpxr7LdlrbrE/edit#slide=id.g105b4fffa32_0_942

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

Testing data models is sometimes like trying to form a bust from clay made of cornstarch and water. Right when you think you've got it into the right shape and set it on a shelf, it completely melts into a puddle of mush. Our practice of testing transformations on top of shifting, changing data falls apart in the same way over and over again, yet we don't learn our lesson. Come learn from Mariah Rogers (Palmetto) why we're doing model testing wrong, how we can change our ways to do it better, and what problems will be essential for the dbt Community to solve together to bridge the gap.

Check the slides here: https://docs.google.com/presentation/d/1oTWnOJxCSRN7ihgI-SflQCBkA7cwmcpGvryOh1vWKoc/edit?usp=sharing

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

The real world is unreliable. Planes take off late, trains leave early, and cars break down. Sometimes, we need to get data from a source without a standard connector. Sometimes, a schedule really doesn't cut it. In this talk, we'll build a pipeline that responds to events to ensure that data is delivered quickly and reliably. We'll also ensure it can handle failure and keep bad data from clogging the plumbing.

Check the slides here: https://docs.google.com/presentation/d/1W9p7H4l0fUr7iAJ3GxEGUTmWGtmc_iu02N-MKb2BSFM/edit?usp=sharing

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

With Trino (formerly PrestoSQL) and dbt combined, you can get faster access to your data and the ability to analyze data across multiple data sources with ease. Extract, load and transform data in your data lakehouse easier than ever before using dbt’s Trino adapter. Join Brian Zhan and Tom Nats as they talk about the new dbt connector for Trino and how it works, along with a demo showing how easy it is to deploy, build and serve up analytics using dbt and Starburst Galaxy.

Check the slides here: https://docs.google.com/presentation/d/1-A-mfc1RIj87ypz6KeZvxK62QLaGthmMqBPy10vNnDk/edit?usp=sharing

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

Do you want to take your dbt project beyond simple unique and not-null tests, but don’t know where to start? Join the dbt Labs team for a deep dive into testing. You’ll learn how to customize tests to fit your unique needs, lean on the amazing dbt community for pre-built tests you can add straight to your project, and flex your Jinja skills by creating your own custom tests. By the end of this course you’ll be walking tall knowing that the data you’re providing to your customers is clean, reliable, and consistent.

Check the slides here: https://docs.google.com/presentation/d/1TCehN5TxHYIuE6gk3rCGx1f9kLkkcXM7TnfcDejUnqo/edit?usp=sharing

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

Description: dbt now supports Python models! In this hands-on workshop you’ll learn how to build your first Python models in dbt, alongside SQL at the center of your transformations.

You’ll learn how to: - Build your Python transformation in a notebook - Add this transformation as a model in your dbt project - Decide between building models in SQL or in Python

Prerequisites: - Basic familiarity with Python and DataFrames - If you want to use your own Warehouse and dbt project, make sure that you have dbt 1.3 installed and have followed the “additional setup” from our docs

Check the slides here: https://docs.google.com/presentation/d/133CVwwAxc5qT80ZJwngQ_ZSikOkCttvzWwGpdZCgOHQ/edit#slide=id.g1693e59a4f4_0_0

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

Allowing more people into the data development process can improve shipment speed, but can also cause some anxiety for folks that wonder how to preserve best practices as participation expands. In his session, Kshitij Aranke (Vouch Insurance), shares how his team created safe inroads to communal development through automated change management on dbt projects that provided automatic best practice checks on each pull request.

Check Google Slides here: https://docs.google.com/presentation/d/17D2DC4KUxfLopYLMvK4ywFVy5MPaPFeRE9fskkir0CM/edit#slide=id.gac0f4c9a75_0_0

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

Analytics work mirrors product development: identify a user need, build a minimum viable product to address that need, evaluate the impact and iterate. In this talk, Michal Kolacek, analytics engineer at Slido describes how MVP-like thinking can help data teams counterbalance and complement the standardized approaches of dbt.

We will walk through Slido’s evolution in their approach, tooling and the vision of building better data products using Deepnote notebooks. Finally, we will take a look under the hood of the new dbt integration in Deepnote and outline how data teams can use it to accelerate model prototyping and metrics workflows.

Check the slides here: https://docs.google.com/presentation/d/1-L7ndud6z5gsFtF3WdjA6AVG40_vrCAcVRNarqWNtPg/edit?usp=sharing

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

The modern data platform elegantly consists of a complex set of elements. It must manage data from multiple source systems existing in different locations that are matched, consolidated, controlled, and packaged with business logic within an infrastructure of varied technologies strung together. Providing evidence and trust, an observability platform with dbt as the hub monitors ELT down to the individual processes. It ensures that SLAs are met regarding availability, throughput, and quality. Come see how Slalom confidently assures the user community that the democratized data there meets organizational standards.

Check Notion document here: https://montrealanalytics.notion.site/Coalesce-Workshop-Guide-6382db82046f41599e9ec39afb035bdb

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

As analytics engineers and data people, we know the value we create in our own blood, sweat, and dbt models. But how is this value actually realized in practice? In this talk, David Jayatillake (Metaplane) draws on his experiences to discuss the processes, ways of thinking, tooling, and governance needed to realize the benefits from analytics engineering work in the greater organization.

Check the slides here: https://docs.google.com/presentation/d/1VmmqNQsrv1t0uuV81O6PJQ1XASyLRGxvAdB8eWIG9TQ/edit?usp=sharing

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

How do you train and enable 20 data analysts to use dbt Core in a short amount of time?

At M1, engineering and analytics are far apart on the org chart, but work hand-in-hand every day. M1 engineering has a culture that celebrates open source, where every data engineer is trained and empowered to work all the way down the infrastructure stack, using tools like Terraform and Kubernetes. The analytics team is comprised of strong SQL writers who use Tableau to create visualizations used company wide. When M1 knew they needed a tool like dbt for change management and data documentation generation, they had to figure out how to bridge the gap between engineering and analytics to enable analysts to contribute with minimal engineering intervention. Join Kelly Wachtel, a senior data engineer at M1, explain how they trained about 20 analysts to use git and dbt Core over the past year, and strengthened their collaboration between their data engineering and analytics teams.

Check the slides here: https://docs.google.com/presentation/d/1CWI97EMyLIz6tptLPKt4VuMjJzV_X3oO/edit?usp=sharing&ouid=110293204340061069659&rtpof=true&sd=true

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