Web Analytics with GA4 and BigQuery Training Course

Course Introduction

Web Analytics with GA4 and BigQuery Training Course is a comprehensive professional program designed to equip digital marketers, web analysts, data analysts, business intelligence professionals, and digital transformation teams with the practical skills required to collect, analyze, query, visualize, and interpret modern website and application analytics data. The course combines Google Analytics 4 measurement concepts with BigQuery data warehousing and SQL analytics to provide a powerful framework for moving beyond standard web reports toward deeper behavioral and performance analysis.

The course begins with the foundations of GA4 measurement, including events, parameters, users, sessions, traffic acquisition, engagement, conversions, audiences, and ecommerce interactions. Participants learn how the event-based GA4 model supports flexible measurement of websites and applications and how properly designed event structures provide the foundation for reliable analysis. The program emphasizes translating business objectives into measurable events, dimensions, metrics, and analytical questions rather than simply collecting large volumes of website activity data.

A central focus is the integration of GA4 with BigQuery. Google Analytics can export raw event data to BigQuery, where the information can be queried using SQL-like syntax and combined with external data sources. Daily exports create events_YYYYMMDD tables, while streaming exports can provide current-day data through events_intraday_YYYYMMDD tables. Participants learn how these structures support scalable behavioral analysis and how export choices, event volumes, processing requirements, and data completeness affect analytical workflows.

The course develops practical SQL and data-engineering skills for web analytics. Participants learn how to work with nested and repeated GA4 fields, extract event parameters, use UNNEST, construct sessions and user-level datasets, aggregate event data, analyze traffic sources, calculate conversion metrics, and build reusable analytical queries. They also learn how to combine GA4 event data with customer, advertising, CRM, ecommerce, product, and other organizational datasets in BigQuery to create richer views of digital performance than isolated platform reporting can provide.

Another major component is advanced web performance analysis. Participants investigate acquisition channels, landing pages, engagement, user journeys, conversion funnels, ecommerce behavior, customer segments, retention, campaign performance, and device or geographic differences. They learn to create analytical datasets and dashboards that help stakeholders understand not only what happened on a website or application, but also which audiences and journeys contributed to important business outcomes. The course also emphasizes efficient BigQuery querying, data validation, appropriate aggregation, and cost-aware analytical practices.

By the end of the program, participants will be able to design a practical GA4 and BigQuery analytics workflow that connects measurement planning, event collection, data export, SQL analysis, validation, visualization, and business interpretation. They will understand how to reconcile GA4 and BigQuery results, investigate discrepancies, develop reusable analytical queries, and transform raw event data into meaningful web intelligence. Google specifically notes that differences between GA4 interface reporting and BigQuery exports can occur because the systems provide different data and processing layers, making reconciliation and validation an important professional skill.

Duration

5 days

Who Should Attend

• Web analysts responsible for measuring website and digital product performance.

• Digital marketing professionals analyzing acquisition, engagement, campaigns, and conversions.

• Data analysts working with web, customer, ecommerce, and behavioral datasets.

• Business intelligence professionals developing digital performance reporting and dashboards.

• Marketing analysts seeking advanced GA4 and SQL-based analytical capabilities.

• Ecommerce analysts measuring product views, shopping behavior, purchases, and customer journeys.

• Digital product managers seeking deeper insight into user behavior and product performance.

• SEO and paid media specialists requiring more detailed website and campaign performance analysis.

• CRM and customer analytics professionals combining web behavior with customer and transactional data.

• Data engineers supporting analytics data pipelines and GA4-to-BigQuery integrations.

• Business managers and decision-makers who need reliable digital performance intelligence.

• Professionals transitioning from traditional Google Analytics reporting to advanced cloud-based web analytics.

Course Objectives

• Develop a comprehensive understanding of GA4's event-based measurement model and apply it to websites, applications, digital products, marketing activities, and business objectives.

• Design effective measurement frameworks covering events, parameters, users, sessions, conversions, ecommerce activities, acquisition sources, engagement, and other important digital interactions.

• Configure and understand GA4-to-BigQuery data export structures, including daily event tables, streaming tables, datasets, export options, and relevant data limitations.

• Write effective GoogleSQL queries for extracting, transforming, aggregating, and analyzing GA4 event data stored within BigQuery's nested and repeated data structures.

• Build user, session, event, acquisition, funnel, ecommerce, and conversion datasets that support advanced web analytics and business intelligence applications.

• Analyze customer journeys, traffic sources, landing pages, engagement patterns, conversions, ecommerce activity, retention, and audience behavior across multiple dimensions.

• Integrate GA4 data with external business datasets in BigQuery to develop broader analytical perspectives covering customers, products, campaigns, transactions, and commercial outcomes.

• Develop reliable analytical validation and reconciliation processes for identifying differences between GA4 reports and BigQuery exports and investigating their underlying causes.

• Optimize BigQuery analytical workflows by applying appropriate filtering, aggregation, partition-aware querying, reusable SQL structures, and cost-conscious data processing practices.

• Complete an applied web analytics project that combines GA4 measurement, BigQuery export data, GoogleSQL analysis, validation, segmentation, funnel analysis, and business intelligence reporting.

Comprehensive Course Outline

Module 1: Foundations of GA4 Web Analytics

• Understanding modern web analytics, GA4's event-based measurement model, users, sessions, events, parameters, dimensions, metrics, conversions, and business objectives.

• Translating organizational goals into measurable digital interactions, key events, conversions, engagement indicators, ecommerce activities, and analytical questions.

• Exploring GA4 reporting structures, acquisition analysis, engagement reporting, user behavior, monetization concepts, audiences, and exploratory analysis.

• Establishing measurement governance covering event naming, parameter standards, conversion definitions, data ownership, documentation, and analytical consistency.

Module 2: GA4 Measurement Planning and Data Collection

• Designing website and application measurement plans that connect business requirements with events, parameters, user properties, conversions, and other analytical data structures.

• Developing consistent event and parameter taxonomies that support meaningful reporting, segmentation, funnel analysis, customer journeys, and long-term analytical requirements.

• Understanding traffic acquisition, campaign parameters, source and medium classifications, landing pages, referral activity, and other acquisition-related dimensions.

• Identifying common implementation problems such as missing events, inconsistent parameters, duplicate tracking, incorrect conversions, and poorly defined measurement requirements.

Module 3: GA4 and BigQuery Integration

• Understanding the process of linking GA4 properties to BigQuery, required project configuration, permissions, data streams, event exclusions, and export settings.

• Exploring the GA4 BigQuery dataset structure, including analytics_<property_id> datasets and daily events_YYYYMMDD event tables.

• Understanding daily, streaming, and available 360 export options, their data availability characteristics, limitations, and implications for analytical workflows.

• Evaluating BigQuery storage and processing considerations, event volumes, export limits, data freshness, and analytical requirements when designing web analytics architectures.

Module 4: GA4 BigQuery Schema and GoogleSQL Fundamentals

• Exploring GA4 event schemas, event timestamps, user identifiers, traffic-source fields, device information, geographic attributes, ecommerce data, and event parameters.

• Working with nested and repeated GA4 structures using GoogleSQL techniques such as UNNEST, field extraction, conditional logic, aggregation, filtering, and grouping.

• Building reusable SQL queries for event counts, users, sessions, traffic sources, landing pages, conversions, engagement, and other common web analytics measures.

• Developing efficient query patterns for large event datasets while controlling unnecessary data scanning, processing requirements, and analytical complexity.

Module 5: User, Session, and Customer Journey Analytics

• Constructing user-level and session-level analytical datasets from raw GA4 events to investigate behavioral patterns and digital engagement.

• Analyzing page and screen interactions, navigation sequences, landing pages, session behavior, engagement, and user activity across different digital experiences.

• Building customer journey analyses that identify common paths, repeated interactions, conversion sequences, and behavioral differences between audience groups.

• Applying segmentation techniques to compare new and returning users, acquisition channels, devices, geographies, customer groups, and other relevant populations.

Module 6: Acquisition, Campaign, Funnel, and Conversion Analytics

• Analyzing source, medium, campaign, channel, landing page, and acquisition performance to understand how users arrive and engage with digital properties.

• Building conversion funnels that measure progression through important website actions and identify drop-off points, bottlenecks, and differences between audience segments.

• Evaluating campaign and channel performance using sessions, users, engagement, conversions, conversion rates, revenue, and other relevant marketing measures.

• Connecting acquisition and conversion analysis with business objectives while recognizing attribution assumptions, data limitations, conversion definitions, and reporting differences.

Module 7: Ecommerce and Advanced Web Performance Analytics

• Analyzing ecommerce events, product interactions, shopping behavior, purchases, revenue, product performance, and customer activity using GA4 data exported to BigQuery.

• Developing product-level and customer-level analytical datasets that support purchase analysis, product performance, repeat behavior, and commercial web intelligence.

• Investigating device, geography, browser, technology, audience, acquisition, and behavioral differences that may influence digital performance and conversion outcomes.

• Combining web analytics with external customer, transaction, advertising, product, or CRM datasets in BigQuery to develop integrated digital performance analysis.

Module 8: Advanced SQL Analytics and BigQuery Optimization

• Developing advanced GoogleSQL queries using common table expressions, window functions, conditional aggregation, date operations, subqueries, joins, and reusable analytical structures.

• Creating daily, weekly, monthly, cohort, retention, funnel, and rolling-period analytical datasets from GA4 event-level data.

• Applying query optimization techniques such as effective filtering, appropriate aggregation, partition-aware querying, selective field usage, and controlled data processing.

• Designing scalable analytical workflows that balance analytical depth, query performance, data freshness, maintainability, and BigQuery processing costs.

Module 9: Data Validation, Reconciliation, and Web Analytics Dashboards

• Comparing GA4 reports with BigQuery event exports to identify discrepancies caused by reporting identity, time zones, excluded streams or events, data processing, and differences in available data.

• Establishing validation procedures for event counts, users, sessions, conversions, acquisition dimensions, ecommerce measures, and other important analytical outputs.

• Designing dashboards and reporting datasets that communicate acquisition, engagement, conversion, ecommerce, audience, and customer journey insights to business stakeholders.

• Developing documentation and quality-control processes that improve confidence in web analytics reporting and make analytical outputs easier to reproduce and maintain.

Module 10: Advanced Web Intelligence Strategy and Applied Capstone

• Designing an end-to-end GA4 and BigQuery web analytics architecture connecting measurement planning, event collection, export, SQL analysis, validation, dashboards, and business decision-making.

• Establishing governance practices for measurement standards, data quality, access management, documentation, query management, reporting consistency, and analytical ownership.

• Completing a practical capstone project using GA4 BigQuery event data to analyze acquisition, engagement, journeys, funnels, conversions, ecommerce performance, and audience behavior.

• Presenting the final analytics solution through optimized SQL queries, validated datasets, dashboards, performance findings, analytical limitations, and actionable recommendations for digital improvement.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.