Google Cloud

Google Cloud Platform services, infrastructure, and data tools (97 posts)

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Measurelab awarded Google Cloud Marketing Analytics Specialisation

At the start of the year, if you’d asked us whether Measurelab would be standing shoulder to shoulder with Europe’s biggest consultancies by September, we would've been surprised. Not because we don't believe in ourselves, but because these things feel so distant - until suddenly, they’re not. So, here it is: we’ve been awarded the Marketing Analytics Services Partner Specialisation in Google Cloud Partner Advantage. What’s the big deal? In Google’s own words (with the obligatory Zs): “Spec

Will Hayes•11 Sept 2025

BigQuery AI.GENERATE tutorial: turn SQL queries into AI-powered insights

BigQuery just got a major upgrade, you can now plug directly into Vertex AI using the new AI.GENERATE function. Translation: your analytics data and generative AI are now best friends, and they’re hanging out right inside SQL. That opens up a whole world of new analysis options for GA4 data, but it also raises some questions: * How do you actually set it up? * What’s it good for (and when should you avoid it)? * Why would you batch the query? Let’s walk through it step by step. Step 1: H

Katie Kaczmarek•3 Sept 2025

Webinar: Stop the martech madness! Go composable. Deliver value faster.

In this 30-minute webinar, we use three real-world examples to demonstrate how a composable approach can help you do more with the data and tech you already have - delivering value at speed. We cover three practical examples of how your marketing data warehouse can support better insights and experiences - without the need for more martech. Learn how you can: * Score wins quickly and regularly * Streamline your martech stack * Stop planning and start building Have questions? Reach out to

Will Hayes•8 Jul 2025

Behind the Cloud – Data Preparations in BigQuery

In this episode of Behind the Cloud, Matt explores BigQuery’s new Data Preparation feature, an AI-powered, point-and-click tool for transforming data with ease. From natural language transformations using Gemini to automated workflows and scheduled outputs, learn how Google is simplifying data prep for analytics and machine learning. Video transcript [00:00:00] Hello and welcome to another episode of Behind the Cloud. Today we are gonna look at a feature or a service, or whatever you wanna ca

Matthew Hooson•24 Apr 2025

Data pipeline optimisation with Google Cloud and Dataform

In our recent engagement with a client, we went on a journey to transform their data pipelines, tackling inefficiencies in performance and cost within their Google Cloud BigQuery environment. Our efforts culminated in a comprehensive optimisation strategy that used Dataform, improved SQL practices, and implemented tailored solutions for significant performance gains and cost savings. Here’s a deep dive into the highlights of our project. Identifying inefficiencies in BigQuery workflows We beg

Prasanna Venkatesan•22 Apr 2025

Dataform for BigQuery: A basic end-to-end guide

Dataform is a powerful tool for managing your data workflows in a structured, version-controlled, and automated way. Whether you're a beginner or an experienced data engineer, Dataform simplifies SQL-based transformations while integrating seamlessly with Google BigQuery. Although this blog offers a basic introduction to Dataform's functionality, users can achieve significantly more with Dataform. From advanced scheduling, parameterised queries, and dependency management to complex data modelli

Prasanna Venkatesan•18 Mar 2025

Behind the Cloud – Releases and scheduling in Dataform

In this episode of Behind the Cloud, Matthew dives into the details of releases and scheduling in Dataform. He breaks down how to manage different versions of your codebase in GitHub. From taking snapshots, to scheduling executions at various intervals daily, hourly, or monthly. By the end of the episode, you’ll have the know-how to confidently release and schedule your code, making it easier to build robust tables and models with Dataform. Video transcript Introduction to releases and sche

Matthew Hooson•7 Mar 2025

2024: Measurelab's year in review

Same same but different At the beginning of the year, I wasn't quite sure what Measurelab would look like by the end of 2024. Altman's assistants had just been unleashed. The robots were on the march. Would the analytics arena be conquered by AI? Would we all be replaced by intelligent agents? As it turns out, no. Things are pretty much the same - on the surface at least. And that's no bad thing. After the tumultuous ups and downs of a rollercoaster 2023, I'll take steady, deliberate progress

Steven Elliott•27 Dec 2024

A step-by-step guide to migrating scheduled queries to Dataform

Managing scheduled queries in BigQuery often feels limiting — there’s no version control, no easy collaboration, and scaling can be difficult. If you’ve ever wondered how to make SQL workflows smoother, Dataform is your answer. In this post, I’ll show you how I migrated a BigQuery scheduled query to Dataform and how it transformed the way I manage my data pipelines. After all, we all want to know who’s been touching our queries, don’t we? Getting started in Dataform First thing you need to

Katie Kaczmarek•27 Nov 2024

How to set up a Dataform repository with GitHub & Google Cloud integration

Setting up a Dataform repository can be challenging without the right steps. Whether you’re new to Dataform or want to optimise your workflow, this guide will show you how to seamlessly connect it with GitHub and Google Cloud (GC). What is Dataform and why use it? Dataform is a powerful tool for managing version-controlled SQL workflows in a collaborative way. GC incorporates BigQuery and GitHub integration, providing an efficient way to organise and maintain complex data pipelines. Let’s bre

Katie Kaczmarek•27 Nov 2024

Behind the Cloud – IAM roles in Google Cloud

In this episode of Behind the Cloud, Matthew dives into Identity and Access Management (IAM) on Google Cloud. He discusses the common frustrations users face, and the significance of assigning specific, granular permissions to mitigate potential risks. Video transcript Introduction to IAM roles [00:00:00] Matt: Hello and welcome to another episode of Behind the Cloud. I’m afraid today isn’t going to be the most glamorous of episodes because what we’re here to talk about today is IAMs on GCP

Matthew Hooson•5 Nov 2024

Integrating siloed data: Springer Nature marketing and sales case study

The Springer Nature Group is an academic publishing company, with brands dating back to 1842, that advances scientific discovery by publishing robust and insightful research, supporting the development of new areas of knowledge, making ideas and information accessible around the world, and leading the way on open access. The challenge The sales and marketing teams depended on incomplete data, which didn’t capture the entire customer journey due to different systems in use. Transactions and re

Mark Rochefort•7 Aug 2024

Behind the Cloud: Using Generative AI in the GCP

In this episode of Behind the Cloud, Matthew delves into the world of generative AI in the Google Cloud Platform, highlighting how Google has integrated generative AI features into its various services. Matthew explores the ways generative AI can be used within BigQuery, such as generating SQL queries and Python notebooks! Video transcript Introduction to Generative AI in Google Cloud [00:00:00] Matt: Hello and welcome to another episode of Behind the Cloud. Uh, today we’re going to cover g

Matthew Hooson•30 Jul 2024

Behind the Cloud: GCP foundational best practice

In this episode of Behind the Cloud, Matt explains how to organise GCP projects by specific use cases, how to automate processes, establish clear naming conventions, and follow best practices around security, tagging, and more. Video transcript Introduction [00:00:00] Matthew: Hello and welcome to another episode of Behind the Cloud. We’ve had a little bit of a brief hiatus but now we’re back and we’re going to do another series of videos. Today we’re going to kick off with what arguably sh

Matthew Hooson•27 Jun 2024

Behind the Cloud: Setting up a Dataform project within BigQuery

In this episode of Behind the Cloud, Matthew demonstrates how to enable and set up a Dataform project within BigQuery, connect it to GitHub, and initialise the workspace for building a Dataform project. Matt walks us through enabling BigQuery, creating a repository, setting up the region, and using service accounts. Video transcript Introduction to Dataform in BigQuery [00:00:00] Matt: Hello and welcome to this week’s behind the cloud sticking with the practical theme today. We’re going to

Matthew Hooson•4 Apr 2024

Customer Data Platforms (CDPs)

Our take on CDPs We’ve been around long enough to have seen the bandwagon-jumping that inevitably happens with any new tech trend as it travels the hype cycle. Right now, Customer Data Platforms (CDPs) are reaching the peak of inflated expectations - and are at risk of descending into the trough of disillusionment. Measurelab doesn’t resell technology licences and we don’t rake in money from vendor kick-backs. So we’re happy to tell it like it is. If you haven’t already got a CDP, you may not

Matthew Hooson•14 Mar 2024

Behind the Cloud: Connecting GA4 to BigQuery

In this episode of Behind the Cloud, Matt explores the practical side of Google Analytics 4 (GA4) and its free export feature to BigQuery. We learn about export limits, batch exports, and streaming options for GA4 data. The episode also touches on setting up BigQuery within a Google Cloud project. Video transcript Introduction to GA4 and BigQuery Export [00:00:00] Matt: Hello and welcome back to Behind the Cloud. This week we’re going to delve into something a little bit more practical. Whe

Matthew Hooson•14 Mar 2024

Behind the Cloud: Dataform, what is it and why does it matter?

In this episode of Behind the Cloud, Matt discusses Dataform, what it is, and why it matters. Video transcript Cloud Data Warehousing [00:00:00] Matt: Welcome to Behind the Cloud. Today we’re exploring data form, but first a little bit of scene setting. Over the past number of years, cloud computing, specifically cloud data warehousing, has advanced significantly. Huge amounts of data can be queried in seconds. The scalability of the platforms is near infinite from both a performance and a

Matthew Hooson•26 Feb 2024

Behind the Cloud: The essentials of Google BigQuery

In this episode of Behind the Cloud, Matt discusses the essentials of Google Cloud’s BigQuery. Everything from project structure, data handling, to understanding the costs involved. Video transcript [00:00:00] Matt: Hello and welcome to Behind the Cloud. Today we’re going to be diving into the nuts and bolts of Google Cloud’s BigQuery and how it can help to revolutionise your marketing analytics. Whether you’re really familiar with the cloud or this is all new to you, this episode aims to gui

Matthew Hooson•7 Feb 2024

Behind the Cloud: What Google Cloud tools should you be familiar with?

In this episode of Behind the Cloud, Matthew aims to answer the question: what are the Google Cloud Platform tools of the marketing analytics trade? And more specifically, what are the tools that you should care about in Google Cloud. For a more in-depth write up on Google Cloud tools, check out Matt’s blog post. Video transcript [00:00:00] Matt: Hello and welcome to today’s episode of Behind the Cloud. We’re going to try and answer the question, what are the GCP tools of the marketing analyt

Matthew Hooson•13 Jan 2024

2023: Measurelab's year in review

2023 was a momentous year for Measurelab. It marked a decade of delivering analytics excellence to the world, a year when we were named one of the UK’s best places to work and became a fully-certified GCP partner, a summer that saw the sunsetting of Universal Analytics, followed by the new dawn of generative AI and the beginning of an augmented analytics era. Into the sunset From the very beginning of January, right up to the deprecation deadline of July 1st, we were swamped with GA4 migratio

Steven Elliott•22 Dec 2023

The Derelict Data Warehouse

A well-maintained and utilised data warehouse is a thing of beauty. Imagine all your data from disparate sources autonomously extracted, loaded and transformed into nice neat reporting tables. Picture, if you can, impactful analysis, company-wide data-driven decision-making, a true understanding of return on ad spend. It’s enough to make anyone weak at the knees. But therein lies the problem. Companies (or ambitious individuals) can be too desperate to reach the promised land and rush headlong

Matthew Hooson•24 Aug 2023

The sun is setting on Universal Analytics

It’s finally happening. Google has announced the sunsetting of Universal Analytics, or more specifically, the date when UA will stop processing new hits. The 1st of July, 2023. For those without a calendar to hand, that’s fifteen and a half months from now. So plenty of time still to think about migrating to Google Analytics 4, right? Wrong. Well, wrong if on 1st July 2023 you want to be able to compare your latest GA4 data with comparable data from the previous year. And what analyst wouldn’

Dara Fitzgerald•16 Mar 2022

Data warehouse: Repair broken tables in BigQuery

At Measurelab, we love a bit of data warehousing using BigQuery; in fact, we are obsessed with finding the best approach to managing data warehouses in the most optimal way possible.  So in this series, we want to share with you our knowledge and expertise to show what a fantastic and dynamic tool BigQuery is. As you may know, BigQuery has some super powerful features, which allow us to build, manipulate and even run machine learning algorithms within the interface. However, we’re all human, an

Lace Rogers•8 Mar 2021

Data warehousing: What is BigQuery and how do I get started?

At Measurelab we live and breathe the Google Cloud Platform, so our specialists are experts in Bigquery.  We have decided in this series to share our knowledge and take you through some great techniques to maintain your BigQuery data warehouse.   So firstly-what is BigQuery? BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. ...and that means? Simply put, BigQuery is a fantastic cloud-based data warehouse in which you can store huge

Lace Rogers•21 Dec 2020

Google Analytics data import: automate data import with Python & Cloud functions

Why automate data import into Google Analytics A few months back I was granted access to a Google Cloud Source Repository (private Git repositories hosted on Google Cloud part of Google’s Cloud developer tools) that contained Python code and configuration details for automating the extraction of data from a BigQuery table and uploading to Google Analytics as a custom dimension via the Management API on a desired schedule. Choosing the right approach for blog word counts Being primarily a Jav

Victor Sarker•16 Nov 2020

How to use BigQuery without GA360: insights from Measurefest 2019

Speaking at Measurefest For the first time in a few years, I took to the stage at Measurefest to talk about how to get your data from Google Analytics into BigQuery, and what you can do with it when you get there. Affordable BigQuery solutions Obviously, Analytics 360 can do this, but it costs $$$ per year. I outlined some more affordable methods, including third-party connector solutions, and provided a detailed example of how we would use our own Pipelines solution and what we could achiev

Adam Englebright•12 Sept 2019

Goodbye DoubleClick, hello Google Marketing Platform!

Last week, Google announced they were unifying their analytics and advertising platforms under a single new name: Google Marketing Platform. The Google Analytics 360 Suite and DoubleClick brands are being replaced with this single name. What does this mean for DoubleClick? If anything this is a change that has needed to happen for years. DoubleClick always sat rather clumsily alongside other tools from Google and this shift heralds the beginning of a more unified approach. Search Ads 360 wil

Mark Rochefort•17 Jul 2018

Data Studio new countries availability

<span style="font-weight: 400;">The time has come for more of you to enjoy the benefits of Data Studio reports! Today, Google has announced long-awaited expansion of its product availability to more than 180 countries. </span> More and more people will now be able to enjoy the benefits of this powerful tool - you can now create, share and edit reports, and impress your boss and clients with your skilful dashboard creation skills. But that's not all! With that great news come other useful f

Magdalena Pajak•7 Mar 2017