List of Google BigQuery Data Transfer Service Customers
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Since 2010, our global team of researchers has been studying Google BigQuery Data Transfer Service customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Google BigQuery Data Transfer Service for iPaaS (Integration Platform as a Service) from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Google BigQuery Data Transfer Service for iPaaS (Integration Platform as a Service) include: Aviva, a United Kingdom based Insurance organisation with 29091 employees and revenues of $53.09 billion, Zenith - The ROI Agency, a United Kingdom based Professional Services organisation with 6000 employees and revenues of $1.00 billion, trivago N.V, a United States based Professional Services organisation with 650 employees and revenues of $80.0 million and many others.
Contact us if you need a completed and verified list of companies using Google BigQuery Data Transfer Service, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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Aviva | Insurance | 29091 | $53.1B | United Kingdom | Google BigQuery Data Transfer Service | iPaaS (Integration Platform as a Service) | 2017 | n/a | In 2017 Aviva implemented Google BigQuery Data Transfer Service as part of an iPaaS (Integration Platform as a Service) initiative to centralize marketing data ingestion and campaign measurement. The Google BigQuery Data Transfer Service pipeline was used to ingest web analytics and advertising platform feeds and to reattribute offline signals into BigQuery datasets, supporting marketing and media operations in the United Kingdom. The deployment emphasized scheduled transfer workflows and dataset staging to populate analytical tables for attribution and campaign analysis, with ETL-style preprocessing and orchestration to maintain consistent ingestion. Integrations explicitly included web and advertising platform data streams and offline conversion records, creating a single ingestion layer for downstream analytics and media optimization, and the project reported improved media efficiency in the UK. | ||
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trivago N.V | Professional Services | 650 | $80M | United States | Google BigQuery Data Transfer Service | iPaaS (Integration Platform as a Service) | 2017 | n/a | In 2017, trivago N.V implemented Google BigQuery Data Transfer Service as part of an iPaaS (Integration Platform as a Service) deployment to automate marketing data ingestion. The deployment targeted automated ingestion of Google advertising and YouTube reporting into BigQuery and established a foundation for a centralized marketing data warehouse. Google BigQuery Data Transfer Service was configured to run recurring scheduled transfers from advertising sources, landing raw reporting extracts into a centralized BigQuery dataset. Configuration emphasized standardized schemas and consistent load patterns to enable downstream analytics and reporting. This setup used native transfer orchestration to reduce manual ETL operations and streamline data capture. The implementation integrated Google advertising and YouTube reporting sources directly with BigQuery, consolidating marketing and advertising reporting workflows across European markets. Operational coverage focused on marketing, analytics, and ad operations teams responsible for campaign performance and reporting. Data accuracy and granularity for reporting and analytics improved as part of this Europe marketing and advertising implementation. Governance practices established centralized transfer scheduling, dataset access controls, and standardized data schemas to support consistent reporting and analysis. The configuration laid the technical groundwork for a marketing data warehouse and enabled teams to consume BigQuery-hosted data for analytics and reporting. | ||
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Zenith - The ROI Agency | Professional Services | 6000 | $1.0B | United Kingdom | Google BigQuery Data Transfer Service | iPaaS (Integration Platform as a Service) | 2017 | n/a | In 2017, Zenith - The ROI Agency implemented Google BigQuery Data Transfer Service to centralize advertising and measurement data pipelines. Zenith used Google BigQuery Data Transfer Service, an iPaaS (Integration Platform as a Service), to consolidate online ad events with offline client signals for marketing analytics and campaign measurement. The implementation focused on automated ingestion of impressions, clicks, and conversion data from Google and DoubleClick, combined with offline client signals to enable unified campaign attribution. Configuration work included scheduled transfer pipelines, schema mapping and normalization into BigQuery tables, and data validation routines to support consistent analytics and reporting. Integrations were explicitly with Google and DoubleClick sources and with client provided offline datasets, supporting a marketing and advertising operational scope based in the United Kingdom. The deployment fed analytics workflows used by media buying and analytics teams, establishing a closed loop media buying system that linked measurement to buying decisions. The project produced a reported outcome for a client example, Aviva, where the closed loop approach contributed to a 15% improvement in measured media efficiency. Governance elements emphasized consistent measurement taxonomy and centralized data validation to maintain signal integrity across campaign optimization workflows. |
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