Trusted Data → Trusted AI: Data Architecture & Integration Patterns
AI models are only as good as the data behind them. Poor data pipelines lead to hallucinations, compliance risks, and broken trust. This workshop shows how to design AI-ready data architectures that deliver clean, governed, and explainable flows across Snowflake, Salesforce Data Cloud, and Neo4j GraphRAG.
You’ll learn integration patterns, governance practices, and observability methods that make LLMs, RAG, and AI agents truly enterprise-ready.
Who Should Attend:
- Architects & Dev Leads
- Enterprise & Data Architects
- Data/AI Engineers building RAG pipelines
- Governance & MDM leaders
Key Outcomes:
- Design zero-copy data flows across Snowflake + Salesforce Data Cloud
- Apply observability & governance to prevent AI failures
- Use GraphRAG with Neo4j for explainability and trust
- Deliver data contracts for agents and RAG pipelines
- Walk away with templates, playbooks, and a 90-day roadmap
Module 1: AI-First Data Architecture
- Data demands of LLMs and agents
- AI-ready vs AI-risky data
- Lake vs warehouse vs lakehouse
Module 2: Integration Patterns
- Batch, streaming, and event-driven pipelines
- Zero-copy Snowflake ↔ Salesforce Data Cloud
- Feeding Agentforce with curated data
Module 3: RAG Systems
- Chunking & embedding patterns
- Vector stores (Pinecone, Bedrock, Weaviate)
- Why stale data = hallucinations
Module 4: Governance & MDM
- Golden IDs and trusted reference data
- PII masking and purpose-based access
- Blueprint: Snowflake + Data Cloud + MDM
Module 5: Observability & Lineage
- Freshness, drift, and schema monitoring
- Tools: Great Expectations, Monte Carlo, OpenLineage
- Incident runbooks for AI pipelines
Module 6: GraphRAG for Explainability
- What is GraphRAG and why it matters
- Demo: Neo4j + RAG with evidence paths
- Making AI auditable and compliant
Module 7: Industry Patterns & Roadmap
- Retail, healthcare, insurance, manufacturing use cases
- 90-day maturity roadmap: quick wins → trusted AI
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.