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· 6 min read
Sanjana Sen
Jason Ganz
David Krevitt

We’ve all done it: fanned out data during a join to produce duplicate records (sometimes duplicated in multiple).

That time when historical revenue numbers doubled on Monday? Classic fanout.

Could it have been avoided? Yes, very simply: by defining the uniqueness grain for a table with a primary key and enforcing it with a dbt test.

So let’s dive deep into: what primary keys are, which cloud analytics warehouses support them, and how you can test them in your warehouse to enforce uniqueness.

· 5 min read
Sanjana Sen
Jason Ganz
David Krevitt

Why primary keys are important

We all know one of the most fundamental rules in data is that every table should have a primary key. Primary keys are critical for many reasons:

  • They ensure that you don’t have duplicate rows in your table
  • They help establish relationships to other tables
  • They allow you to quickly identify the grain of the table (ex: the customers table with a PK of customer_id has one row per customer)
  • You can test them in dbt, to ensure that your data is complete and unique

· 4 min read
David Krevitt

I’ve used the dateadd SQL function thousands of times.

I’ve googled the syntax of the dateadd SQL function all of those times except one, when I decided to hit the "are you feeling lucky" button and go for it.

Missed Coalesce?

The annual conference dedicated to the advancement of analytics engineering wrapped up on December 10th.

Watch the talks