Azure Data Platform Engineering
8-module course for platform engineers: Azure provisioning, identity management, Unity Catalog admin, compute optimization, network security, data integration, monitoring, and DR. 45 hours.
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Azure Data Platform Engineering
Thank you for purchasing this course from Datanest Academy!
Getting Started
1. Review course.yaml for the complete course outline, learning objectives, and prerequisites
2. Start with modules/module-01-*.md and progress through each module in order
3. Each module includes hands-on exercises, code examples, and production patterns
Course Structure
course.yaml— Complete course metadata, outline, and prerequisitesmodules/— 8 progressive modules (full premium content)free-preview/— Redacted preview versions (for sharing with colleagues)assets/— Supporting materials
Module Format
Each module contains:
- Learning objectives
- Concept explanations with real-world context
- Production-ready code examples
- Hands-on exercises
- Key takeaways and review questions
Support
Questions? Email support@datanest.dev
License
Copyright (c) 2026 Jesse Mikkola / Datanest Academy. All rights reserved.
This course content is licensed for personal and organizational use only.
Redistribution is not permitted.
📄 Content Sample guide/01-workspace-provisioning-and-infrastructur.md
Chapter 1: Workspace Provisioning and Infrastructure as Code
Duration: 45-60 minutes | Difficulty: Intermediate | Prerequisites: Basic familiarity with Azure, Databricks, Terraform, Unity Catalog, Bicep
Learning Objectives
By the end of this chapter, you will be able to:
1. Define the core architectural patterns and principles
2. Design a reference architecture aligned to business requirements
3. Identify the appropriate building blocks for each layer
4. Evaluate trade-offs between different design approaches
5. Create an implementation roadmap from architecture to production
6. Apply Azure patterns to production scenarios
1. Understanding the Fundamentals
Before diving into implementation, it is essential to establish a solid conceptual foundation. Workspace Provisioning and Infrastructure as Code forms a critical pillar of the Azure Data Platform Engineering framework, and getting the fundamentals right determines the success of everything built on top.
1.1 Core Concepts
The core concepts underlying this chapter are rooted in established industry patterns and best practices. Each concept builds on the previous one, creating a coherent framework for reasoning about complex systems.
| Concept | Description | Application |
|---|---|---|
| Foundation Layer | The core primitives and building blocks | Establish base capabilities for all higher-level patterns |
| Integration Layer | Interfaces and connectors between components | Define clear boundaries and contracts between subsystems |
| Orchestration Layer | Coordination and workflow management | Manage multi-step processes with error handling |
| Observability Layer | Monitoring, logging, and tracing | Provide visibility into system behavior and performance |
| Governance Layer | Policies, controls, and compliance | Ensure consistent operation within organizational guardrails |
1.2 Why This Matters
In production environments, getting this wrong has measurable consequences. Teams that implement these patterns correctly experience:
- Reduced incident frequency by 40-60% through proactive detection
- Faster mean-time-to-resolution through structured procedures
- Higher team confidence through documented and tested runbooks
- Lower operational overhead through automation and standardization
2. Implementation Walkthrough
... and much more in the full download.