Why Your Looker Dashboards Should Be Code

My journey into data analytics — and my first experience with Looker — began quite unexpectedly. My background is in software development and quality assurance, but I had never worked closely with data or even heard of Looker before.

That changed when I was given the opportunity to take on a data analyst role, where one of my first tasks was to quickly build an important report. I was told it would be simple — just some copying, pasting, and adding a few KPIs. The tool of choice was Looker, described as something easy to pick up.

Now, after spending some time learning (and unlearning) along the way, I’d like to share what I wish I had known from the very beginning — so you can avoid some of the same pitfalls in your own Looker journey.

A Quick Introduction to Looker

If you’re just starting to explore this tool, here’s what you need to know: Looker is a Google Cloud-owned data analytics platform for data exploration and visualization. It features its own semantic layer, many useful features (which I’m still discovering), and a powerful, yet not always straightforward, way of working.

I’ve found that having a background in software development can sometimes make adapting to Looker’s logic a bit tricky. Looker uses a domain-specific language called LookML, which comes in slightly different formats for different Looker components. For example, the syntax for dimensions and measures in view files differs from the syntax…