AWS re:Invent 2025 - Scaling Data Transformation w/ dbt & Nasdaq: Unlocking Ent Power Global Mkts

Scaling Data Transformation with dbt & Nasdaq: Unlocking Enterprise Power for Global Markets

Introduction to Nasdaq

• Nasdaq is a global financial technology company with three main pillars:
  1. Market Services: Owns and operates major trading markets in North America and Europe
  2. Capital Access Platforms: Responsible for listings and index services
  3. Financial Technology: Provides solutions and services to ~4,000 customers globally

Nasdaq Eclipse Intelligence Platform

• Nasdaq's Eclipse Intelligence Platform provides data management, analytics, reporting, and billing capabilities for Nasdaq's customers
• Key components of the platform:
  1. Data Management: Ingests data from Nasdaq products and customer sources, stores in a cloud data lake, and provides access endpoints
  2. Analytics: Delivers business insights and enables both traditional dashboards and AI/agent-based use cases
  3. Reporting: Automates report generation and distribution for customers
  4. Billing: Manages transaction-based and non-transactional billing for customers

Role of dbt in the Eclipse Intelligence Platform

• Nasdaq's goals in leveraging dbt:
  1. Integrate with existing Nasdaq products and services
  2. Provide better business models and analytical capabilities for customers
  3. Enable internal and external users to extend and participate in model creation
  4. Enforce standards and contracts for data access and AI/agent use cases
• Strategic vision:
  1. Provide faster innovation to customers by managing the data platform and baseline models
  2. Unify the "financial fabric of the globe" with standard data semantics and ontologies
  3. Enable a "data model marketplace" where customers can create and share custom models

dbt Architecture and Implementation

• Nasdaq uses a "hybrid tenant" approach, with shared multi-tenant services and single-tenant customer data
• dbt is also deployed in a similar hybrid model:
  1. Nasdaq maintains a central dbt account for core model development and testing
  2. Customers are provided their own dbt accounts, pre-configured with Nasdaq's data contracts and models
• Nasdaq's dbt project structure:
  1. Nasdaq-provided data layer: Maps Nasdaq's transactional data to business-friendly terms
  2. Nasdaq standard analytical models: Baseline models covering 80% of common use cases
  3. Customer-extended models: Allows customers to build custom models or extend Nasdaq's models
  4. Semantic layer: Provides contextual knowledge and enforces data usage standards

Key Value Drivers and Metrics

• Measure customer success in areas such as:
  1. Easy access to data and understanding of the data
  2. Increased engagement and effectiveness of AI/agent-based use cases
  3. Enabling new customer data access services
  4. Reusability of Nasdaq's data models across customers
  5. Empowering non-technical users through no-code experiences
  6. Ensuring data is purpose-built and trustworthy for customer use cases

Conclusion

Nasdaq is leveraging dbt as a key component of its Eclipse Intelligence Platform to enable faster innovation, unify global financial data semantics, and create a "data model marketplace" for its customers. By providing a hybrid, multi-tenant dbt implementation, Nasdaq aims to deliver easy access to high-quality data, empower customers to build custom analytics, and drive new data-driven use cases and revenue streams.