London, UK · Serving UK/EU · GBP pricing

BigQuery consultant. GA4 to BigQuery integration & querying.

Q: How much does BigQuery cost to run?

BigQuery charges for data storage (around £0.02 per GB/month) and queries (£5 per TB scanned). For typical GA4 implementations, monthly costs range from £20-200 depending on query volume and optimization. Cost controls and optimization are implemented to keep expenses predictable.

Q: Do we need data engineering resources to use BigQuery?

Not necessarily. Turnkey solutions are built including pre-built queries, documentation, and training so marketing teams can use BigQuery effectively. For more complex needs, recommendations can be provided for when additional engineering support makes sense.

Q: Can you integrate our CRM data with GA4 in BigQuery?

Yes. CRM data (Salesforce, HubSpot, etc.), advertising platform data, product catalogs, and other sources are regularly integrated with GA4 in BigQuery, enabling unified analysis across the customer journey.

Turn your GA4 data into a strategic asset with BigQuery.

Google Analytics 4's interface is limited. The reports are rigid, sampling kicks in at scale, and the data expires after 14 months. For businesses that need deeper analysis, longer retention, or integration with other data sources, BigQuery is the answer.

Marc Alexander is an independent BigQuery consultant with nine years of experience helping businesses move beyond GA4's limitations. He specialises in connecting GA4 to BigQuery, transforming raw event data into structured analytics tables, writing custom SQL queries that answer real business questions, and building data infrastructure that scales with growth.

Based in London and working across the UK and EU, Marc helps businesses implement BigQuery properly, optimize query costs, integrate multiple data sources, and train teams to extract insights that GA4's interface simply cannot provide.

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What Marc does as a BigQuery consultant

GA4 to BigQuery connection and setup

Marc configures the native GA4 to BigQuery export, ensuring data flows correctly, setting up appropriate dataset locations for compliance, managing access permissions, and establishing monitoring to catch export failures before they become data gaps.

BigQuery data modeling and transformation

Raw GA4 exports are deeply nested and difficult to query. Marc transforms this data into clean, structured tables that marketing and analytics teams can actually use—flattened event tables, sessionised data, user-level aggregations, and custom dimensions that make analysis straightforward.

Custom SQL query development

When GA4 reports can't answer business questions, Marc writes custom SQL queries to extract the insights needed. This includes complex user journey analysis, cohort analysis, multi-touch attribution modelling, funnel analysis with custom definitions, and revenue analysis that matches business logic.

BigQuery cost optimisation

BigQuery charges by data scanned, and poorly written queries can become expensive fast. Marc optimizes query performance through partitioning strategies, clustering configurations, materialized views, and query pattern analysis to keep costs under control as data volumes grow.

Multi-source data integration

BigQuery's real power comes from combining GA4 data with other sources. Marc integrates CRM data, advertising platform spend, product data, customer support metrics, and offline conversion data into unified BigQuery datasets that enable true cross-channel analysis.

Dashboard and reporting on BigQuery data

Marc builds custom dashboards using Looker Studio, Power BI, or Tableau connected directly to BigQuery, creating visualizations that update automatically and bypass GA4's sampling and reporting limitations entirely.

BigQuery training and enablement

Teams shouldn't depend on consultants for every query. Marc provides SQL training tailored to GA4 data structures, teaches teams to write their own queries, documents common analysis patterns, and builds query templates that non-technical users can modify.

Data governance and access management

Marc implements proper data governance frameworks in BigQuery, setting up appropriate access controls, creating separate datasets for different teams, implementing row-level security where needed, and ensuring compliance with data protection regulations.

Why businesses hire Marc as their BigQuery consultant

GA4's interface limitations are blocking analysis

The standard GA4 interface cannot answer complex questions about user behaviour, customer lifetime value calculations, or custom attribution models. Marc connects GA4 to BigQuery and builds the SQL queries that extract insights GA4's reports cannot provide.

Data sampling is making GA4 unreliable at scale

When GA4 properties receive significant traffic, reports start sampling data, making analysis unreliable. BigQuery provides access to complete, unsampled data regardless of volume, and Marc ensures teams can query this data efficiently.

Need to keep GA4 data beyond 14 months

GA4 deletes data after 14 months, making year-over-year analysis and long-term trend identification impossible. Marc implements BigQuery storage that retains data indefinitely while managing storage costs appropriately.

Marketing data is siloed across platforms

GA4 shows website behaviour, advertising platforms report spend and conversions, the CRM tracks sales outcomes, but nothing connects. Marc integrates these sources in BigQuery, creating unified datasets that show the complete customer journey.

Need custom attribution that matches business reality

Standard last-click or data-driven attribution doesn't reflect how businesses actually acquire customers. Marc builds custom attribution models in BigQuery that weight touchpoints according to business logic and experimental evidence.

Trying to calculate accurate customer lifetime value

True LTV calculation requires combining GA4 acquisition data with transaction history, repeat purchase patterns, and retention metrics. Marc implements LTV models in BigQuery that account for these factors and update continuously.

BigQuery costs are spiraling out of control

Without proper optimization, BigQuery queries can scan terabytes of data unnecessarily, creating significant costs. Marc audits query patterns, implements partitioning and clustering, and restructures tables to dramatically reduce scanning costs.

Teams lack SQL skills to use BigQuery effectively

BigQuery is powerful but requires SQL knowledge that marketing teams often don't have. Marc bridges this gap through training, documentation, and building query templates that teams can use without deep technical expertise.

How Marc approaches BigQuery consulting

Marc's approach to BigQuery consulting starts with understanding what questions the business needs answered that GA4 cannot provide. Rather than simply connecting systems, he designs data architectures that support specific analytical use cases.

Every BigQuery implementation considers data structure, query patterns, cost implications, and team capabilities. Marc builds solutions that balance analytical power with practical usability, ensuring teams can actually leverage the data once it's in BigQuery.

Data transformations are documented and version controlled. SQL code follows clear naming conventions, includes inline documentation, and is written to be maintainable by others. The goal is creating data infrastructure that outlasts any individual consultant.

Marc works closely with marketing, analytics, data engineering, and finance teams to ensure BigQuery implementations deliver ROI through better decisions, not just better data availability.

Marc's GTM expertise includes

GA4 to BigQuery native export configuration and monitoring

BigQuery dataset design and table optimization

SQL query development for complex GA4 analysis

Data modeling and transformation using SQL

Partitioning and clustering strategies for cost optimization

Scheduled queries and data pipeline automation

Multi-source data integration (CRM, advertising, product data)

Custom attribution modelling in BigQuery

Customer lifetime value calculation and prediction

Cohort analysis and retention metrics

User journey and funnel analysis with custom definitions

BigQuery access management and permissions

Looker Studio and Power BI integration with BigQuery

BigQuery cost monitoring and optimization

SQL training for marketing and analytics teams

Data governance frameworks for BigQuery

Real-time data streaming into BigQuery

Machine learning on GA4 data using BigQuery ML

BigQuery implementation process

Discovery and requirements (Week 1)

Marc reviews current analytics setup, identifies analytical gaps that BigQuery can solve, documents specific questions the business needs answered, and assesses team capabilities for ongoing BigQuery usage.

Architecture design (Week 1-2)

Working with stakeholders, Marc designs the BigQuery data architecture, including dataset structure, transformation logic, data refresh schedules, access controls, and integration points with other systems.

GA4 BigQuery connection (Week 2)

Marc configures the GA4 to BigQuery export, selects appropriate dataset location for compliance, sets up monitoring for export failures, validates data is flowing correctly, and establishes baseline query patterns.

Data transformation and modeling (Week 2-4)

Marc builds SQL transformations that restructure raw GA4 exports into usable analytical tables. This includes sessionisation logic, user-level aggregations, custom event parsing, and any business-specific metrics or dimensions.

Query development and optimization (Week 3-5)

Marc develops SQL queries that answer specific business questions, implements partitioning and clustering for cost efficiency, creates query templates for common analyses, and documents query patterns for team use.

Integration and dashboard building (Week 4-6)

If needed, Marc integrates additional data sources, builds dashboards on top of BigQuery data, and creates scheduled reports that deliver insights automatically without manual querying.

Training and handover (Week 5-6)

Marc provides SQL training tailored to GA4 data structures, documents the BigQuery architecture, creates query examples and templates, and trains teams on cost-efficient querying practices.

Optimization and monitoring (Ongoing)

Marc monitors query costs, optimizes expensive patterns, updates transformations as business needs evolve, and provides ongoing support as teams build BigQuery competency.

BigQuery consultant pricing

Marc offers flexible BigQuery consulting based on project scope and complexity:

GA4 BigQuery Connection Setup: £500 - £1,200

Basic configuration of GA4 to BigQuery export, dataset setup, permissions configuration, and validation that data is flowing correctly. Includes initial documentation.

BigQuery Data Transformation Package: £1,500 - £3,500

Custom SQL transformations that restructure raw GA4 data into analytical tables, including sessionization, user aggregations, and business-specific metrics. Pricing depends on complexity.

Custom SQL Query Development: £800 - £2,500

Development of specific SQL queries to answer business questions, including complex analysis like attribution modeling, cohort analysis, or LTV calculation. Priced per analytical requirement.

BigQuery Cost Optimisation Audit: £600 - £1,500

Comprehensive review of BigQuery usage patterns, identification of expensive queries, implementation of partitioning and clustering strategies, and documentation of cost-efficient query patterns.

Multi-Source Data Integration: £2,000 - £5,000

Integration of additional data sources (CRM, advertising platforms, product data) into BigQuery alongside GA4, including data pipeline setup and unified data models.

BigQuery Training Workshop: £800 - £1,500/day

Hands-on SQL training for teams, tailored to GA4 data structures and common analytical needs. Includes query templates and ongoing documentation.

Complete BigQuery Implementation: £3,500 - £8,000

End-to-end BigQuery setup including GA4 connection, data transformations, cost optimization, dashboard building, and team training. Pricing varies based on scope and data complexity.

Ongoing BigQuery Support: £800 - £2,000/month

Monthly retainer for ongoing query development, optimization, new data source integration, and technical support as analytical needs evolve.

All pricing is in GBP. Projects are scoped individually based on specific requirements and data volumes.

Common BigQuery questions

How much does BigQuery cost to run?

BigQuery charges for data storage (very cheap, around £0.02 per GB/month) and queries (£5 per TB scanned). For typical GA4 implementations, monthly costs range from £20-200 depending on query volume and optimization. Marc implements cost controls and optimization to keep expenses predictable.

Do we need data engineering resources to use BigQuery?

Not necessarily. Marc builds turnkey solutions including pre-built queries, documentation, and training so marketing teams can use BigQuery effectively. For more complex needs, he can recommend when additional engineering support makes sense.

How long does GA4 data take to appear in BigQuery?

GA4 exports to BigQuery daily, with data typically appearing within 24 hours. Intraday tables provide access to data from the current day, though with some limitations. Marc ensures teams understand data freshness and can work within these constraints.

Can BigQuery replace GA4 entirely?

Not completely. GA4's interface is still useful for quick checks and exploratory analysis. BigQuery is for deeper analysis, longer retention, custom metrics, and multi-source integration. Most businesses use both, leveraging each for its strengths.

What happens to our data if we stop using BigQuery?

Data in BigQuery is yours and persists until you delete it. If you stop the GA4 export, historical data remains accessible. Marc ensures implementations are documented so data can be accessed even without ongoing consultant support.

How difficult is SQL for non-technical teams?

Basic SQL for GA4 analysis is learnable with proper training. Marc provides query templates, documentation, and training that enables marketing teams to run common analyses independently. Complex queries can be templated for easy reuse.

Can you integrate our CRM data with GA4 in BigQuery?

Yes. Marc regularly integrates CRM data (Salesforce, HubSpot, etc.), advertising platform data, product catalogs, and other sources with GA4 in BigQuery, enabling unified analysis across the customer journey.

How do you ensure BigQuery stays GDPR compliant?

Marc implements data governance frameworks including appropriate access controls, data retention policies, anonymization where required, and dataset locations within EU regions for GDPR compliance. BigQuery provides robust tools for data protection when configured correctly.

Why BigQuery matters for serious analytics

GA4's interface is designed for general use cases, not specific business needs. BigQuery removes these constraints entirely.

With BigQuery, businesses can analyze complete user journeys across multiple sessions, calculate custom metrics that match business definitions, build attribution models that reflect reality, integrate offline conversion data, retain data indefinitely for trend analysis, query millions of events without sampling, and answer complex questions that GA4's interface simply cannot handle.

For businesses that make data-driven decisions at scale, BigQuery transforms GA4 from a reporting tool into a strategic analytical asset.

Ready to make your analytics decision-grade?

Book a free 30-minute consultation to discuss your BigQuery challenges and explore how Marc can help.

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He's surprisingly friendly, even when telling you your BigQuery's a disaster.

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