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Topic

Monte Carlo

data_observability data_reliability data_quality

2

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2020-Q1 2026-Q1

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Filtering by: dbt Coalesce 2022 ×
Building a Data Platform from Scratch with dbt, Snowflake and Looker

When Prateek Chawla, founding engineer, joined Monte Carlo in 2019, he was responsible for spinning up our data platform from scratch. He was more of a backend/cloud engineer, but like with any startup had to wear many hats, so got the opportunity to play the role of data engineer too. In this talk, we’ll walk through how we spun up Monte Calro’s data stack with Snowflake, Looker, and dbt, touching on how and why we implemented dbt (and later, dbt Cloud), key use cases, and handy tricks for integrating dbt with other popular tools, like Airflow, and Spark. We’ll discuss what worked, what didn’t work, and other lessons learned along the way, as well as share how our data stack evolved over time to scale to meet the demands of our growing startup. We’ll also touch on a very critical component of the dbt value proposition, data quality testing, and discuss some of our favorite tests and what we’ve done to automate and integrate them with other elements of our stack.

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

Field-level lineage with dbt, ANTLR, and Snowflake

Lineage is a critical component of any root cause, impact analysis, and overall analytics heath assessment workflow. But it hasn’t always been easy to create, particularly at the field level. In this session, Mei Tao, Helena Munoz, and Xuanzi Han (Monte Carlo) tackle this challenge head-on by leveraging some of the most popular tools in the modern data stack, including dbt, Airflow, Snowflake, and ANother Tool for Language Recognition (ANTLR). Learn how they designed the data model, query parser, and larger database design for field-level lineage—highlighting learnings, wrong turns, and best practices developed along the way.

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