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 the slides here: https://docs.google.com/presentation/d/1xJEyfg81azw2hVilhGZ5BptnAQo8q1L7aDLGrnSYoUM/edit?usp=sharing

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

Python model support is one of the hottest topics in the dbt Community Slack right now—but also one of the most intangible. What’s possible? What’s practical? What’s the point? In this session, Eda Johnson (Snowflake) will show how Snowpark Python further enhances a dbt + Snowflake development experience by supporting new workloads, including Machine Learning within your dbt DAGs.

Check the slides here: https://docs.google.com/presentation/d/1IJSeE96bze7DECuDYqsTVv6FaOcNcJ5tTiCWKEku_QQ/edit#slide=id.g14034313943_0_36

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

The Databricks Lakehouse Platform unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. Databricks now includes complete support for dbt Core and dbt Cloud and you will hear from Conde Nast using dbt and Databricks together to democratize insights. We will also share best practices for developing and productionizing dbt projects containing SQL and Python, governing data with standard SQL, and exciting features on our roadmap such as materialized views for Databricks SQL.

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

Historically, analytics has been focused on "what happened." And to this day, newer and newer generations of tooling, dbt for example, have come forth accelerating the speed and utility of data in an enterprise for decision making. Machine learning, on the other hand (the "what will happen"), has seemingly been stood up as a separate silo with an organization with seemingly "more intricate" technical requirements, the need for "data scientist", and done so all in the name of how to handle "more special" data resulting in "more accurate" decision making. In this session, you will learn how to cut through the noise and extend and leverage your analytic practice with Snowflake and dbt Labs into the realm of machine learning by pairing your analytical pipelines with a feature store layer to declaratively serve both model training and model scoring scenarios, even at some of the lowest latency (real-time) production requirements.

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/1H-aPsc2DkPGcJUV4pd_iLSdMMMAMZTEtsAFO4hpglXM/edit#slide=id.g15a4510fa6a_0_560

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/.

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/.

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 the contemporary world of machine learning algorithms - “data is the new oil”. For the state-of-the-art ML algorithms to work their magic, it’s important to lay a strong foundation with access to relevant data. But the skills required to make those datasets meaningful for machine learning...that's an art.

Join Jigyasa Grover and Rishabh Misra of Twitter as they talk about the power of the most fundamental aspect of machine learning—dataset curation—and walk through the process of constructing good quality datasets with a hands-on Pythonic example.

Check the slides here: https://docs.google.com/presentation/d/1HOii7Z_F-75euxcjIY2H6OmJ6EsYLOLRLutMxGcrW_Y/edit?usp=sharing

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