How-To Coalesce Replay Tracks: Sessions for the Team Preparing to Scale Four modules designed to help the established analytics engineer plan for rapid growth.
Product News NEW dbt Learn courses & badging now available! dbt Labs now offers five free courses for the emerging analytics engineer. Those new to dbt will find everything they need to get started (and badged!) in our dbt Learn Fundamentals course, while seasoned users can go deeper on topics like macros, materializations, and project refactoring.
Product News Adopting CI/CD with dbt Cloud Choosing between continuous delivery and continuous deployment based on business needs
How-To How I set up my conformed dimensional models A startup's guide to modeling data following Kimball best practices
How-To How to find a role in analytics engineering This article is written for job seekers. I’ve gathered a lot of data over the course of a month-long search and learned about what the landscape looks like for the analytics engineer hiring pipeline.
How-To The farm-to-table testing framework: How to catch data quality issues before they break your dashboards A holistic data testing framework to help you catch data quality issues before they impact your stakeholders.
How-To Modeling marketing attribution Marketing attribution has long been one of the stickiest problems in analytics. But with raw data, SQL, and dbt a previously complex problem can become beautifully simple.
How-To Modeling subscription revenue If you’re a data analyst at a SaaS company or an ecommerce business with a subscription component, it is inevitable that you will be asked to analyze metrics like churn, upgrades, and downgrades. Here's how to do this with dbt.
How-To How great data teams test their data models Analytics code is code. Which means that it will have bugs. And without rigorous processes in place to find and eliminate those bugs, code quality will degrade over time.
How-To Four questions to help accurately scope analytics engineering projects Data teams are successful when they build reserves of trust. One important way to build trust is by consistently delivering projects on time. Here are four questions we've found to be useful in helping us spot the potholes that derail analytics engineering projects.
How-To How to track data changes with dbt snapshots All data analysts have faced the problem–how do I model data when the record in the data warehouse keeps changing? In this post, I'll cover how to solve this using dbt snapshots.
How-To How to review an analytics pull request Version control is a critical part of the software engineering workflow, but for many analysts, writing and reviewing pull requests is still a relatively new habit. Here's a checklist we use to review analytics PRs.
Building data teams How to hire an analytics engineer Modern data warehouses have upended the way that data teams function. Increasingly, companies are hiring a new kind of technical analyst to bridge the gap between data engineers and data analysts. Here's why and how you can hire one too.
How-To Data testing: why you need it and how to get started Advice from analysts and data engineers at HubSpot, Managed by Q, GitLab, Wong Decision Intelligence, AskWonder, and Calogica
How-To How Monzo, the UK’s favorite mobile-only bank, is rolling out dbt Stephen Whitworth, Data Engineering Lead at Monzo, spoke at the London dbt Meetup a few weeks ago. Here are my thoughts on his talk and what the dbt community can learn from it.
How-To How to unnest arrays in Redshift Unnesting arrays on Redshift is a pain, but it’s doable. This post walks through the entire process, start to finish.
How-To How compatible are Redshift and Snowflake’s SQL syntaxes? I just went through the process of converting 25,000 lines of SQL from Redshift to Snowflake. Here are my notes.
How-To One analyst's guide for going from good to great If you’re a hotshot junior analyst and you want a guide for breaking through this skills plateau, this guide is for you.
How-To How to safely convert strings to integers in Redshift This is a very stupid problem. I am not writing this post because it’s a fascinating topic—rather, I’m writing it in the hopes that you avoid the headaches I've gone through.
How-To “How do you decide what to model in dbt vs LookML?” I got this question on my last post. It is a good one, and one that I’ve gotten a bunch of times over the past year and a half. This post is my attempt to answer it.
How-To How to Integrate dbt and Looker with User Attributes dbt and Looker were built with the same ethos: analysts should be working in code.
How-To How to design your Looker Explores Frequently asked questions about Looker explores and how to design them very well.
How-To Installing dbt packages Want to go from syncing new data to having transformed data models built in minutes? Packages are going to be your friend.
How-To The most underutilized function in SQL Over the past nine months I’ve worked with over a dozen venture-funded startups to build out their internal analytics. In doing so, there’s a single SQL function that I have come to use surprisingly often.
