One strategy we use at Montreal Analytics to help data teams be more active in designing their information architecture is standardizing how they order columns in their tables and views. Learn about our structure and example with dbt: mtla.pro/3JXLkii

Effectively naming pull requests and their associated commits is crucial in any software development project. Simplify reviewing, improve traceability, and standardize scoping with our tips on effective pull request naming. Read on our blog: mtla.pro/3yfQDmv

Wherever you are on your Looker journey, we’ve got you covered. Our March Looker bootcamps are now open for registration! Spots are limited, register now: mtla.pro/3m4ICOr

Joining a new company is never easy, let alone after switching industries entirely. Alfredo Di Massimo, as a new Analytics Engineer at Montreal Analytics, understands those challenges well. Read about Alfredo's onboarding experience in our BEAM Journal: mtla.pro/3Iu0Zni

Backlogs can be overwhelming to manage, especially when you don't know what questions you are trying to answer. Our Product Owner TJ Quan shares key questions you should be asking yourself to make the most out of your data team. Read on our blog: mtla.pro/3Sch7hM

Goodbye pre-commit-dbt, welcome dbt-checkpoint! We have joined forces with @Datacoves to merge our efforts on pre-commit-dbt, which we will now be co-maintaining under the name dbt-checkpoint. For more information , continue reading on our blog: mtla.pro/3lf6MFp

Snowflake clones are a great way to enhance dbt development, simplifying your workflow and making it more cost-efficient and production-like. More on our blog: mtla.pro/3X3Xmtr

Byte spillage, cost inefficiencies, slow & queued workloads...How can we use Snowflake and dbt to address these challenges? In case you missed our webinar with @SnowflakeDB and @getdbt, access the full synopsis and recording here: mtla.pro/3kWdeB7

⏳ In 2 hours, our first webinar of 2023 with @dbt_labs and @SnowflakeDB is starting! Sign up while you can: mtla.pro/3WOZoi1

One week to go! Don't forget to sign up for our webinar with @dbt_labs and @SnowflakeDB 👉mtla.pro/3WOZoi1

From continuous integration (CI) to data observability, more and more teams are focusing on validating and verifying their data. Here’s the state of testing for data teams as we look into 2023. Read on our blog: mtla.pro/testing-2023

Intermediate models are both the glue or the bridge that holds your pipeline together. Our Senior Data Consultant Jeremie @_jpineau shows ways to leverage intermediate models to improve a dbt project. Read on our blog: mtla.pro/blog-intermediate

Looker? Data Studio? Looker Studio? Our Data Consultant Wei Wei walks you through Google's latest announcement on Looker Studio in our new blog. Read now 👉 mtla.pro/Looker-Studio

To avoid inconsistencies and delays, we need best practice standards and a way to enforce them automatically. In our new blog post, our Data Consultant Dang walks you through dbt best practices and how we use dbt-gloss to keep our projects consistent. mtla.pro/dbt-gloss-blog

Happy Canadian Thanksgiving! We are thankful for our wonderful team and all their hard work. Wishing everyone a restful weekend as we reminisce on memories from our offsite 💜