Data Intelligence End-to-End with Azure Databricks and Microsoft Fabric

This Azure architecture blog was written in collaboration with: Isaac GritzI am a Senior Solutions Architect at Databricks.

Data Intelligence End-to-End Architecture provides a scalable and secure foundation for analytics, AI, and real-time insights from batch and streaming data. The architecture seamlessly integrates with Power BI and Copilot across Microsoft Fabric, Microsoft Purview, Azure Data Lake Storage Gen2, and Azure Event Hubs to support data-driven decision making across the enterprise.

architecture

Data Flow

1. ingestion:
   1. Ingest raw streaming data from Azure Event Hubs Delta Live Table ~ inside Delta Lake Tables that ensure governance Unity Catalog.
   2. Incrementally ingest unstructured and semi-structured data from Data Lake Storage Gen2. Auto loader ~ inside Delta LakeMaintain consistent governance. Unity Catalog.
   3. Seamlessly connect and collect data from relational databases. Lakehouse Union ~ inside Delta LakeEnsures unified governance across all data sources.
2. Process batch and streaming data at scale using: Delta Live Table And high performance Photon Engine next time Medallion Architecture:
   1. Bronze: Raw data for preservation and appreciation
   2. Silver: Clean, Filter, and Combine Data
   3. Gold: Dimensional Model or Aggregated Business Ready Data
3. Save all your data Delta Lake UniformOpen storage format for Azure Data Lake Gen2, supporting Delta Lake, Iceberg, and Hudi for cross-ecosystem compatibility.
4. heighten:
   1. Perform exploratory data analysis, collaborate in real time, and train AI models using serverless collaboration Laptop.
   2. Manage versions and manage AI models, features, and vector indices using: ML Flow, Feature store, Unity Catalogand Vector Search.
   3. Deploy and monitor production AI models. Complex AI System Supports batch processing and real-time deployment Model provided and Lakehouse Monitoring.
5. Deliver ad hoc analytics and BI with high concurrency directly from your data lake. Databricks SQL Serverless.
6. Data analysts use Power BI and Copilot within Microsoft Fabric to create reports and dashboards.
   1. Gold data is accessed and managed live via: Publishing Power BI Semantic Models Connected Unity Catalog and Databricks SQL.
7. Business users Databricks AI/BI Genie Gain natural language insights from your data.
8. Share data securely with external customers or partners. Delta ShareAn open protocol that ensures compatibility and security between various data consumers.
9. Databricks Platform
   1. Unified Orchestration for Data and AI Databricks Workflow
   2. Integrated high-performance computing layer Photon Engine
   3. Unified Data and AI Governance Unity Catalog
10. Posting metadata Unity Catalog Gain visibility across your data assets with Microsoft Purview.
11. Azure Platform
    1. Through ID management and SSO (single sign-on) Microsoft Entre ID
    2. Cost and Billing Management Microsoft Cost Management
    3. Monitor telemetry and system health. Azure Monitor
    4. Manage your encrypted keys and secrets Azure Key Vault
    5. Facilitates version control and CI/CD. Azure DevOps and GitHub
    6. Guaranteed through cloud security management Microsoft Defender for Cloud

component

This solution uses the following components:

Scenario Details

This solution demonstrates how to democratize data and AI while meeting the requirements for enterprise-grade security and scalability by combining Azure Databricks Data Intelligence Platform and Power BI. This architecture achieves this by starting with an open, integrated Lakehouse foundation managed by Unity Catalog. The Data Intelligence Engine then leverages the uniqueness of an organization’s data to provide simple, robust, and accessible solutions for ETL, data warehousing, and AI, enabling organizations to deliver data products faster and easier.

Potential Use Cases

This approach can be used for:

• Modernize your existing data architecture by combining ETL, data warehousing, and AI to create a simpler, future-ready platform.

• Implement real-time analytics use cases such as large-scale e-commerce recommendations, predictive maintenance, and supply chain optimization.

• Build production-grade Gen AI applications such as AI-powered customer service agents, personalization, and document automation.

• Empower business leaders across your organization to gain insights from data without the need for deep technical skills or custom dashboards.

• Securely share or monetize data with partners and customers.