<div class="gn-article"><div class="gn-hero gn-reveal"> <div class="gn-hero__image"><img src="https://cdn.prod.website-files.com/687a235da6861294eec73166/69089aa200b2a3e1175b1e76_65e126ea5e31806eb87ff1ad_e019d08c5452-GW4_Webinars_BigQuery_3._An_intro_to_BigQuery%2520(1).png" alt=""></div> <div class="gn-hero__head"> <span class="gn-kicker"><span class="dot"></span>Event · Expression</span> <h1 class="gn-title">An Introduction to BigQuery</h1> <div class="gn-meta"> <strong>The GO Network</strong> <span class="pip"></span> <span>21 March 2024</span> <span class="pip"></span> <span>1 min read</span> </div> </div> </div> <div class="gn-event-meta gn-reveal"><div class="gn-event-meta__block"> <span class="gn-event-meta__label">When</span> <span class="gn-event-meta__value gn-date">Thu, 21 Mar 2024 · 11:00</span> </div><div class="gn-event-meta__block"> <span class="gn-event-meta__label">Where</span> <span class="gn-event-meta__value">Online</span> </div><div class="gn-event-meta__block"> <span class="gn-event-meta__label">Status</span> <span class="gn-event-status gn-event-status--recording">Past · Recording</span> </div></div> <div class="gn-body"> <h2>Why Agency Leaders Need to Understand BigQuery (Not Just Their Data Teams)</h2> <p>There is a common pattern in agencies: someone mentions BigQuery in a meeting, and the room quietly defers to the data analyst in the corner. Leadership nods along, the conversation moves on, and a significant capability goes underutilised at the strategic level. That pattern is worth breaking. Understanding what BigQuery actually does, and what it makes possible for agency reporting and client analytics, gives decision-makers a sharper grip on the work and a stronger voice in conversations about data infrastructure.</p> <p>This article draws on an introductory session hosted by a member of <strong>The GO Network</strong>'s Agency Network, designed to bring non-technical agency professionals up to speed on BigQuery's practical value for website and app analysis.</p> <h2>What BigQuery Is and Why It Matters for Agency Work</h2> <p>BigQuery is Google's cloud-based data warehouse. It is built to handle very large datasets quickly, running queries across millions of rows of data in seconds without requiring the user to manage servers or storage infrastructure. For agencies, the most immediate application is in marketing analytics: pulling together data from Google Analytics 4, Google Ads, app platforms, and other sources into a single environment where it can be queried, combined, and interrogated at a level of detail that standard dashboard tools simply do not allow.</p> <p>The shift from Universal Analytics to GA4 made BigQuery more relevant than ever for agencies. GA4's native interface limits how far you can drill into raw event data. BigQuery removes that ceiling. Every user interaction captured by GA4 can be exported into BigQuery and queried directly, meaning you can answer questions that the GA4 interface cannot easily surface: multi-session conversion paths, custom funnel analysis, cohort behaviour over extended time periods, and cross-platform attribution that accounts for both web and app activity.</p> <p>For agencies managing analytics on behalf of clients, this matters for two reasons. First, it enables more rigorous performance reporting. Second, it creates an opportunity to offer a genuinely differentiated service. Clients who have experienced only dashboard-level reporting often do not know what deeper analysis looks like until you show them.</p> <h2>Three Areas Where BigQuery Delivers Real Analytical Depth</h2> <h3>1. Raw Event-Level Data Access</h3> <p>Standard analytics interfaces show you aggregated summaries. BigQuery gives you the underlying event data in full. This means you can segment and filter in ways that are not possible through a reporting UI, combining dimensions and conditions freely to answer specific client questions. If a client wants to understand the exact sequence of interactions that precedes a high-value conversion, or how behaviour differs between users on a specific device type in a particular region, that analysis lives in the raw data, not in a pre-built report.</p> <h3>2. Cross-Source Data Joining</h3> <p>One of BigQuery's most valuable capabilities for agencies is the ability to join datasets from multiple sources in a single query. You can combine GA4 event data with CRM exports, ad spend data from Google Ads or paid social platforms, and offline conversion data. This is where meaningful attribution work happens. Rather than relying on platform-native attribution models that each favour their own channel, you can build analysis that reflects the full picture of how a campaign is performing across touchpoints.</p> <h3>3. Scalable Reporting Infrastructure</h3> <p>For agencies running analytics across multiple client accounts, BigQuery provides a consistent infrastructure that scales without the data volume limitations that affect standard analytics tools. Large e-commerce clients, app-heavy businesses, and any client with high traffic volumes will quickly hit the boundaries of what dashboard tools can handle. BigQuery is designed for exactly these environments, and building your agency's reporting capability around it positions you to handle complex clients with confidence.</p> <h2>Practical Steps for Bringing BigQuery Into Your Agency</h2> <p>If your agency has not yet integrated BigQuery into its analytics workflow, the entry point is straightforward. GA4 has a native BigQuery export feature that can be enabled directly within the GA4 property settings. Once activated, raw event data begins flowing into a linked BigQuery project on a daily basis. From there, data can be queried using SQL, connected to visualisation tools such as Looker Studio, or used as the foundation for more advanced modelling work.</p> <p>For agency leaders who are not writing queries themselves, the priority is ensuring your team has the access and the brief to use this capability. A few concrete actions worth considering:</p> <ul> <li>Audit which client accounts currently have the GA4 to BigQuery export enabled, and enable it for those that do not. Raw data cannot be retroactively exported, so starting the feed early preserves future analytical options.</li> <li>Identify one or two high-value client questions that your current reporting cannot answer, and use those as the brief for an initial BigQuery analysis. A focused use case is more persuasive than a general demonstration.</li> <li>Build a basic Looker Studio dashboard connected to a BigQuery query so that non-technical stakeholders, both internal and client-side, can interact with the output without needing to understand the underlying process.</li> <li>Consider the commercial framing. Agencies that can offer raw-data analysis and custom attribution modelling have a tangible differentiator in new business conversations, particularly with clients who have outgrown generic reporting.</li> </ul> <p>BigQuery is not a specialist tool reserved for data engineers. It is a practical capability that, when embedded into agency analytics workflows, raises the quality of insight available to your team and the value you can demonstrate to clients. The sessions run through <strong>The GO Network</strong>'s Agency Network are designed to make this kind of capability accessible to the full range of agency professionals, not just those with a technical background. If your agency has not yet explored what BigQuery makes possible, that is the place to start.</p> </div></div> <aside class="gn-related gn-reveal" data-auto="related-reading"> <div class="gn-related__label">Related reading</div> <ul class="gn-related__list"> <li class="gn-related__item"> <a href="/articles/an-introduction-to-looker-studio" class="gn-related__link"> <span class="gn-related__category">Expression</span> <span class="gn-related__title">An Introduction to Looker Studio</span> <span class="gn-related__excerpt">Connect GA4 to Looker Studio and build performance dashboards your whole team can use. 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