LSEG’s financial data is made available in Databricks via Delta Sharing. The partnership aims to make it easier for financial institutions to build AI-driven applications.
The London Stock Exchange Group (LSEG) and Databricks have partnered to make financial data available within the Databricks platform. The integration is enabled through Delta Sharing, an open standard for sharing live data. Initially, this includes datasets such as Lipper Fund Data & Analytics and Cross Asset Analytics. Additional data—such as reference data, pricing information, models, and tick history—will follow later.
Financial Data
LSEG provides financial data and market infrastructure to clients worldwide. The company offers datasets on funds, market prices, historical transactions, and credit risk, among others. By making this information available in Databricks, financial institutions that are Databricks customers gain direct access via the platform. They can then combine LSEG data with their own enterprise data to develop applications for risk management, compliance, portfolio steering, and trading analytics.
The data is shared via Delta Sharing. That is Databricks’ method for securely and real-time exposing datasets without vendor lock-in. Users can find the data in the Databricks Marketplace, reducing the time spent on data preparation—a major challenge in the industry.
Compatible with Agents
According to Databricks, Agent Bricks plays a central role in the partnership. The tool allows users to build AI agents. These agents can optionally leverage both internal enterprise data and LSEG datasets. They support real-time analytics, scenario modeling, transaction monitoring, and automated reporting. Databricks recently acquired Tecton to expand its agents’ capabilities.
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The partnership targets several clear use cases, including AI-assisted investment analysis, real-time trading analytics, and automated risk management. With this integration, LSEG can bring its data to market in a new way, while Databricks can attract customers with direct access to a relevant niche dataset within its own platform.