Master data integration and AI solutions using Azure Databricks with Microsoft Fabric, enabling faster insights through Unity Catalog, optimized data engineering, and seamless Power BI analytics.
- Introduction to Azure Databricks and Microsoft Fabric
Overview of Azure Databricks
Introduction to Microsoft Fabric and its integration with Databricks
Benefits of using Databricks and Fabric for data engineering and AI
- Setting Up Your Lakehouse Environment
Creating and configuring a workspace in Azure Databricks
Introduction to Unity Catalog for data governance and management
Connecting Microsoft Fabric with your Lakehouse
- Data Engineering with Azure Databricks
ETL processes using Azure Databricks
Optimizing data pipelines for performance and scalability
Data transformation and preparation using Spark
- Leveraging Unity Catalog for Data Governance
Setting up and managing data permissions with Unity Catalog
Implementing data lineage and audit logging
Best practices for catalog management
- Implementing AI Solutions in Databricks
Introduction to machine learning workflows in Databricks
Training and deploying models in a collaborative environment
Using MLflow for model management
- Integrating Microsoft Fabric with AI and Data Solutions
Building seamless data flows between Fabrics and Databricks
Using connectors and data streams for real-time data processing
Enhancing AI capabilities with Microsoft Fabric's built-in analytics tools
- Power BI and Data Visualization
Integrating Power BI with Azure Databricks for analytics
Creating interactive dashboards and reports
Sharing insights and collaborating with stakeholders
- Case Studies and Practical Applications
Real-world use cases for Databricks and Microsoft Fabric
Best practices for achieving rapid insights and delivering value
- Performance Optimization and Best Practices
Optimizing workloads for cost and efficiency
Monitoring and maintaining performance in your Lakehouse environment
Strategies for scaling your data and AI solutions
- Capstone Project
Designing and implementing a comprehensive data solution using Azure Databricks and Microsoft Fabric
Presenting your project and deriving insights from implemented solutions
- Course Review and Next Steps
Recap of key concepts and skills acquired
Exploring advanced topics and further learning opportunities
Q&A session and feedback collection
