S&P Global is opening up its treasure trove of market intelligence to more data scientists—this time through Google Cloud’s BigQuery platform. The move, announced today, is part of the financial data giant’s push to make its AI-Ready Data portfolio accessible wherever customers already work.
The first wave of this partnership makes S&P Global Commodity Insights data available directly in BigQuery, Google Cloud’s autonomous data and AI engine. That means customers can tap into energy and commodity datasets—spanning everything from oil and gas to metals and agriculture—without wrangling messy exports or legacy pipelines.
Cleaner Data, Faster Models
The pitch is simple: S&P Global supplies trusted, structured datasets designed for machine learning; Google Cloud supplies the horsepower to crunch them. For customers, that means faster model training, improved governance and compliance, and sharper decision-making in volatile markets.
Mark Eramo, Co-President of S&P Global Commodity Insights, framed it as both convenience and competitiveness: “By making our AI-Ready Data available through Google Cloud’s BigQuery platform, we’re empowering organizations to harness Google Cloud’s advanced data and AI capabilities alongside our comprehensive commodity data to drive innovation and competitive advantage.”
Why It Matters
For years, S&P Global’s data has been a must-have in industries like energy, finance, and agriculture—but often delivered in formats that weren’t exactly friendly for modern AI pipelines. The AI-Ready Data format, developed by S&P Global’s Enterprise Data Organization, is designed specifically for machine learning applications, providing clean and structured feeds that plug straight into cloud AI platforms.
This move also fits a bigger industry trend: major data providers are racing to embed themselves deeper into the AI and cloud ecosystems where customers are already building models. Bloomberg, FactSet, and Refinitiv have all made similar moves with cloud partnerships. The difference here is S&P Global’s focus on commodities—an area where AI-driven forecasting and risk modeling could be particularly impactful given today’s volatile energy and supply chain markets.
What’s Included
The AI-Ready Data packages now available on BigQuery cover:
- Energy, power, and gas
- Metals and chemicals
- Agriculture and supply chain
- Specialized commodity markets
Customers can use BigQuery to query, prototype, and experiment with these datasets inside Google Cloud’s infrastructure, eliminating friction in moving from raw data to actionable insights.
The Bottom Line
For businesses navigating unpredictable commodity markets, the S&P Global–Google Cloud tie-up offers a faster way to test, model, and act on critical data. For S&P, it’s another step in ensuring its datasets aren’t just valuable, but also cloud-native and AI-ready—a must if it wants to remain indispensable in the era of machine learning-driven decision-making.
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