Use Google’s BigQuery to make sense of all of your data and make better decisions

We have more data at our fingertips than ever before: From website analytics and paid campaigns to CRM records and product usage metrics. However, this can actually make uncovering data insights a fragmented, confusing, and time-consuming process. This can make it challenging to turn numbers into confident, actionable decisions.

Tools like Looker Studio and Power BI can help to visualise your data, which is a great help in understanding what’s going on, but how do you bring the data together in the first place? Complex data warehouses require experienced data engineers and architects, while Excel and Google Sheets simply do not have the processing power required. That is where BigQuery comes in. Think of it as a cloud repository for data of all shapes and sizes. You can use it to bring your data together in one place, and help you make sense of it so you can focus on what really matters: making better decisions. At Box UK, we have helped clients of all sizes to use BigQuery to do just this.

Read this article to see how you can get started with BigQuery in just a few steps.

Getting Started with BigQuery

Setting up BigQuery is easier than many think, and it can quickly become the central hub for all your data. Depending on the size of your data, you might not have to pay anything at all to use it. 

The first step is to create a project in Google Cloud Platform (GCP) and enable BigQuery. From there, you can link your Google Analytics account, so your web event data flows straight in. You can also connect other systems via the GCP API to bring in CRM records, advertising data, or other external data sources. If coding is not your strong suit, tools with user-friendly interfaces such as Zapier, Power Automate, or IFTTT can automate imports, ensuring everything ends up in one place without the need for heavy engineering. With your datasets in BigQuery, you are ready to begin exploring and analysing them!

Exploring Data

You do not need to be a full-time data engineer to start uncovering insights, either. A basic grasp of SQL can take you a long way. Queries using just SELECT, FROM, and WHERE clauses are often enough to start to reveal useful patterns. Wildcards can help you begin to combine multiple days or tables into a single query. If spiralling costs are a concern, scheduled queries and materialised tables keep usage under control and make repeated analysis quicker. 

For those wanting to move faster still, AI agents are now available, which can generate queries for you, meaning you can spend less time writing code and more time interpreting results. Gemini is built into BigQuery, or you can use another LLM outside of BigQuery and paste in the suggested queries. Simply provide a prompt like, “Imagine you are a SQL engineer using BigQuery. Using GA4 data, write me a query that shows how many new users visited the website over the last 30 days”.

Visualising Insights in Looker Studio

Once you have your queries running in BigQuery, the next step is to turn those results into something visual for others to understand. Connecting BigQuery directly to Looker Studio makes it straightforward to build dashboards and reports that automatically update as new data arrives. Creating charts and tables around your key metrics allows teams to explore results interactively with filters and date ranges without looking at raw data. Sharing dashboards also ensures everyone is working from the same, reliable source of truth. At Box UK, we specialise in creating visual representations of data, and love working with our clients to ensure that we surface the most important insights, which enables them to make crucial decisions faster.

Ready to get started? Follow our quick checklist below.