Clearing 2026: why UK universities need recruitment intelligence
UK universities face a deficit crisis. Student Recruitment Intelligence can transform Clearing from chaos to precision.

If you're just here for the screen orientation CASE formula to use in Google Data Studio, here it is:
CASE
WHEN CAST(REGEXP_REPLACE(Screen Resolution, 'x.*', '') AS NUMBER)<CAST(REGEXP_REPLACE(Screen Resolution, '.*x', '') AS NUMBER) THEN "Portrait"
ELSE "Landscape"
ENDDigging into it a bit further, the way tis works is that it takes the bit before the ‘x’ of the Screen Resolution dimension (the x-axis), and sees if it’s smaller than the bit after the ‘x’ (the y-axis). So if the x-axis is less than the y-axis the screen orientation is portrait, otherwise it’s landscape.
I’m using the Universal Analytics dimension 'Screen Resolution' in this example, but you can swap out that for any other reference you have, as long as it has the same format of ‘AxB’ - i.e. 900x800. You can even swap out the 'x' if there is another delimiter in your data. This screen orientation calculation is agnostic and easily changed to fit whatever your data looks like.
In Data Studio, you can add this in the data source itself, or as a custom calculation in any chart as such:

Using this newly created dimension, you can use them in charts to break down any data into landscape and portrait.

It's also useful in tables where you can use it as a filter to give the viewer a different way to view device data. For example:


A small improvement on the formula at the top of this post is below where it accounts for square resolutions too! Not that it occurs frequently to be honest, but it's all about being precise.
CASE
WHEN CAST(REGEXP_REPLACE(Screen Resolution, 'x.*', '') AS NUMBER)<CAST(REGEXP_REPLACE(Screen Resolution, '.*x', '') AS NUMBER) THEN "Portrait"
WHEN CAST(REGEXP_REPLACE(Screen Resolution, 'x.*', '') AS NUMBER)>CAST(REGEXP_REPLACE(Screen Resolution, '.*x', '') AS NUMBER) THEN "Landscape"
ELSE "Square"
ENDThey do exist though:

We cover this example and lots of others in our Data Studio Kickstarter training course. If you'd like to book in the training for your team, or have any questions about it, please get in touch.
UK universities face a deficit crisis. Student Recruitment Intelligence can transform Clearing from chaos to precision.
If you’d told me five years ago that I’d be forecasting product demand using a model trained on 100 billion time points… without writing a single line of ML code… I probably would’ve asked how many coffees you’d had that day ☕️ But its a brand new world. And it’s possible. Let me explain What is TimesFM? TimesFM is a new foundation model from Google, built specifically for time-series forecasting. Think of it like GPT for time, instead of predicting the next word in a sentence, it predicts t
You’ve probably heard that AI is coming to make our lives easier, especially in tools like BigQuery. But here’s the thing: AI isn't magic. If you want it to be accurate and useful, you need to set it up for success. One of the best ways to do that? Improve the metadata in your BigQuery warehouse. Metadata is like the index or contents page in a book, it quickly tells you exactly what’s inside and where to find it. Creating clear metadata means AI can more easily understand your data warehouse