Data quality testing: Where and why you should have it
Data quality testing is the practice of using code-based and automated data quality tests to know whether these assertions you make about your data are valid.
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Recent Posts
We’ve revamped our Professional Services offerings
The Professional Services team at dbt Labs has a simple remit: ensure dbt Cloud customers get as much value from the platform as possible, as quickly as possible.
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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.
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Data Org Structure Examples
The data team is a brand new thing: it’s not IT, it’s not finance...so who does it report to? How big is it?
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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.
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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.
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Hiring an Analytics Engineer
How to screen for curiosity when making your next analytics engineering hire (example interview questions included).
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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.
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Centralized vs Decentralized Data Teams
Over the last four years, the data team at Snaptravel has grown from one analyst to almost a dozen, and they've experimented with five data team structures.
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