Zero Copy changes how architects design for data scale and performance. Learn when to federate, file, cache, or ingest data and how each approach affects Flow, segmentation, and identity.
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Featured Sessions
Scale Trusted AI Adoption with Salesforce and AWS
Learn how to deploy Anthropic models via Amazon Bedrock in Agentforce’s secure environment, enabling compliant AI adoption at scale, particularly for regulated industries.
Prompt to Agent with Google Cloud: Gemini 3 in Agentforce
Explore the full agent development stack using Gemini 3 as the reasoning backbone, prompt builder for Agentforce agents. See Gemini 3 Flash’s fast, high-accuracy inference to build adaptable agents.
More Output, Same Control: Embracing AI-Driven Change
AI will multiply your rate of change. As the bottleneck shifts from writing code to governance, learn how to stay in control of accelerated delivery and focus on the work that needs you.
Building AI-Ready DevOps: L-Founders' Journey to Agentforce
See how L-founders leverage Copado to build an intelligent DevOps foundation, enabling them to deploy Agentforce agents seamlessly with enhanced dependency analysis and advanced debugging capabilities
Optimizing Salesforce’s Own Sales Cloud with Hubbl
See how Salesforce uses Hubbl to accelerate planning. Learn how the internal product team aligns complex requirements to architecture to de-risk and optimize global Sales Cloud updates.
Architecture: AI, Data, Lakehouse, Zero Copy
Modern Data Architecture for AI. Learn from real Enterprise customer stories: Zero Copy to Databricks & Snowflake, real-time lakehouse from scale to latency, amalgamation of customer data, and more.
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Apply Zero Copy: Federate, File, Cache or Ingest
, Director, Product Management, Salesforce
, Director, Salesforce
Role: Architect
Products: Data 360
Topic: Integration
Session Level: Intermediate
Session Type: Theater
- Wednesday, Apr 153:00 PM - 3:20 PM PDT(10:00 PM - 10:20 PM GMT)Theater 4 (Level 2)FIRST COME FIRST SEATED
Session Summary: The session provided a comprehensive overview of Data Cloud's Data 360 capabilities, emphasizing its zero copy data virtualization feature, which enables users to access and process data without duplicating it. Attendees learned about when to use zero copy based on factors such as data size, use case complexity, and real-time requirements, with detailed comparisons between Query Federation and File Federation modes. Practical examples, such as using IoT data for personalized customer experiences, illustrated the efficiency of zero copy in handling large datasets and optimizing compute costs. Additionally, the session highlighted best practices for implementation, such as leveraging caching for frequently accessed data, optimizing query pushdowns, and managing data locality to reduce costs and improve performance.
Key Takeaways:
• Zero copy in Data 360 allows for seamless data virtualization, enabling access to data across systems like Snowflake, Databricks, and Google BigQuery without the need for duplication, thereby reducing costs and improving efficiency.
• Query Federation is ideal for smaller, real-time queries with datasets under 100 million rows, while File Federation is better suited for large-scale datasets and scenarios requiring change data capture (CDC).
• Best practices such as caching frequently accessed data, optimizing query filters with pushdowns, and aligning storage regions with Data Cloud tenants are essential for cost-effective and performant zero copy implementations.
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