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Learn how to design and implement data modeling strategies in Azure Databricks with Unity Catalog, including ingestion patterns, table formats, partitioning, slowly changing dimensions, and clustering strategies.

Units in this learning path:

• Introduction
• Design Data Ingestion Logic
• Choose Data Ingestion Tool
• Choose Data Table Format
• Design Data Partitioning Scheme
• Choose Scd Type
• Implement Slowly Changing Dimension Type 2
• Design Temporal History Table
• Choose Granularity
• Choose Managed Vs Unmanaged Tables
• Design Clustering Strategy
• Exercise
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 137 minutes

Learn how to design and implement robust data pipelines using Lakehouse architecture principles, medallion architecture, and Lakeflow pipelines in Azure Databricks.

Units in this learning path:

• Introduction
• Design Order Operations Pipeline
• Choose Notebook Vs Lakeflow Pipelines
• Design Task Logic Lakeflow Job
• Design Error Handling Pipelines
• Create Pipeline Notebook Precedence
• Create Pipeline Lakeflow Declarative
• Exercise
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 96 minutes

Learn how to design and implement database objects in SQL Server, Azure SQL, and SQL databases in Microsoft Fabric, including tables, indexes, constraints, and specialized table types.

Units in this learning path:

• Introduction
• Understanding Platform Choices
• Design Implement Tables
• Design Implement Indexes
• Specialized Table Types
• Design Implement Constraints
• Design Implement Json
• Design Implement Partitioning
• Exercise Create Database Objects
• Knowledge Check
• Summary

Products: SQL Server, Azure SQL Database, Azure SQL Managed Instance, Fabric

Roles: Data Engineer, Database Administrator, Developer, Solution Architect

Level: Intermediate, Advanced

Subjects: Databases, Data Management, Data Engineering, Cloud Computing, App Development

Duration: 98 minutes

Implement intelligent search capabilities in SQL Server and Azure SQL by combining traditional full-text search with semantic vector search. Learn to choose search approaches, prepare SQL for vector search, and implement vector, hybrid, and ranking-based search patterns.

Units in this learning path:

• Introduction
• Choose Intelligent Search Approach
• Implement Full Text Search
• Prepare SQL Vector Search
• Implement Vector Search Query Patterns
• Implement Hybrid Search Ranking
• Exercise Implement Intelligent Search
• Knowledge Check
• Summary

Products: Azure, Azure SQL Database, SQL Server

Roles: Developer, Data Engineer

Level: Intermediate

Subjects: Databases, Artificial Intelligence, Cloud Computing

Duration: 84 minutes

Integrate AI models with Azure SQL Database using external models, the vector data type, and built-in AI functions. Design embedding strategies, generate embeddings from text, and implement maintenance patterns.

Units in this learning path:

• Introduction
• Understand Evaluate Models SQL Database Workloads
• Create Manage External Model SQL
• Design Embeddings SQL Database Workloads
• Generate Maintain Embeddings SQL Database Workloads
• Exercise Generate Update Embeddings SQL
• Knowledge Check
• Summary

Products: Azure, Azure SQL Database

Roles: Developer, Data Engineer

Level: Intermediate

Subjects: Databases, Artificial Intelligence, Cloud Computing

Duration: 61 minutes

You learn to design and implement private access to Azure Services with Azure Private Link, and virtual network service endpoints.

Units in this learning path:

• Introduction
• Explain Virtual Network Service Endpoints
• Define Private Link Service Private Endpoint
• Integrate Private Link Dns
• Exercise Restrict Network Paas Resources Virtual Network Service Endpoints Using
• Exercise Create Azure Private Endpoint Using Azure Powershell
• Summary

Products: Azure Private Link, Azure Virtual Network

Roles: Administrator, Network Engineer

Level: Intermediate

Subjects: Data Engineering, Networking

Duration: 42 minutes

Create semantic models that serve reliable, governed analytics at scale — from initial DAX logic through performance optimization, data access control, and automated lifecycle management.

Modules in this learning path:

• Dax Power Bi Create Calculations
• Design Semantic Models Scale
• Optimize Semantic Model Performance
• Enforce Semantic Model Security
• Manage Semantic Model Lifecycle

Products: Fabric

Roles: Data Analyst

Level: Intermediate

Subjects: Data Analytics, Data Modeling

Duration: 381 minutes

Design dimensional models and apply transformations using dataflows, Spark notebooks, and T-SQL to produce consistent, analysis-ready data in Microsoft Fabric.

Modules in this learning path:

• Choose Data Store Fabric
• Design Dimensional Models Fabric
• Fabric Transform Data Dataflows
• Fabric Transform Data Notebooks
• Fabric Transform Data Tsql

Products: Fabric

Roles: Data Analyst, Data Engineer

Level: Intermediate

Subjects: Data Analytics, Data Engineering, Data Integration, Data Modeling

Duration: 314 minutes

Azure Architects design and recommend data integration solutions.

Units in this learning path:

• Introduction
• Solution Azure Data Factory
• Solution Azure Data Lake
• Solution Azure Data Brick
• Solution Azure Synapse Analytics
• Design Strategy for Hot Warm Cold Data Path
• Design Azure Stream Analytics Solution for Data Analysis
• Knowledge Check
• Summary Resources

Products: Azure, Azure Blob Storage, Azure Data Factory, Azure Data Lake, Azure Databricks, Azure Stream Analytics, Azure Synapse Analytics

Roles: Solution Architect

Level: Advanced

Subjects: Data Management

Duration: 53 minutes

Build applications with Azure DocumentDB. Create and configure clusters, perform CRUD operations, connect with SDK, design efficient data models, and optimize query performance.

Modules in this learning path:

• Introduction Azure Documentdb
• Create Configure Azure Documentdb Cluster
• Query Manipulate Data Azure Documentdb
• Build Applications Azure Documentdb Sdks
• Model Data Relationships Azure Documentdb
• Apply Schema Design Patterns Azure Documentdb
• Recognize Avoid Schema Design Anti Patterns Azure Documentdb
• Optimize Query Performance Indexes Azure Documentdb

Products: Azure Documentdb

Roles: Developer

Level: Intermediate

Subjects: Databases

Duration: 488 minutes

A data model workshop is part of Success by Design. This module will provide a basic description of data modeling for Microsoft Dynamics 365 and insight into how you can conduct a data model workshop.

Units in this learning path:

• 1 Introduction
• Overview
• 2 Workshops
• 2 1 Out of Box Custom Tables
• 2 2 Table Configuration
• 3 Check
• 4 Summary

Products: Dynamics 365, Dynamics Sales, Customer Insights Journeys, Dynamics Customer Service, Dynamics Field Service, Dynamics Finance, Dynamics Scm, Dynamics Project Operations, Dynamics Commerce, Dynamics Human Resources

Roles: Solution Architect, Functional Consultant

Level: Advanced

Subjects: Data Modeling, Business Applications

Duration: 61 minutes

Learn dimensional schema types, fact and dimension table design, and slowly changing dimension patterns for analytics workloads in Microsoft Fabric.

Units in this learning path:

• Introduction
• Describe Schema Types
• Design Fact Tables
• Design Dimension Tables
• Implement Slowly Changing Dimensions
• Exercise
• Knowledge Check
• Summary

Products: Fabric

Roles: Data Analyst, Data Engineer

Level: Intermediate

Subjects: Data Modeling

Duration: 63 minutes