🥽 AZ-305: Data & Analytics Services — Deep Dive
Study Notes & Exam Prep — 2026 Edition
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- 🎯 Purpose: Deep-dive study notes covering six Azure Data & Analytics services heavily tested in the AZ-305: Designing Microsoft Azure Infrastructure Solutions exam.
- 📅 Version: 2026
- ✍️ Author: Marco Grimaldi
- 🌐 Published: 🥽 AZ-305: Data & Analytics Services — Deep Dive
- 🔗 Companion repos: 📘 AZ-305 Study Notes · 🥽 AZ-305: Azure Compute Services — Deep Dive · 🥽 AZ-305: Azure Messaging Services — Deep Dive · 🥽 AZ-305: Migration, HA & BCDR — Deep Dive · 📘 AZ-104 Study Notes
🗺 What’s in This Repository?
This companion repository to the AZ-305 Study Notes zooms into Azure Data & Analytics — a cluster of services spanning relational databases, data integration, real-time stream processing, big-data warehousing, unified analytics, and IoT ingestion.
| File | Coverage |
|---|---|
| 🛢️ 01 — Azure SQL | SQL Database, Managed Instance, SQL Server on VM — tiers, HA, Geo-replication, SKUs |
| 🔀 02 — Azure Data Factory | Pipelines, datasets, linked services, IR types, triggers, monitoring |
| 🔊 03 — Azure Stream Analytics | Streaming jobs, windowing, inputs/outputs, scaling, compatibility |
| 🏭 04 — Azure Synapse Analytics | Dedicated/serverless SQL pools, Spark pools, pipelines, Link, Studio |
| 🧱 05 — Azure Databricks | Workspaces, clusters, Delta Lake, Unity Catalog, SKUs, security |
| 📡 06 — Azure IoT | IoT Hub, IoT Central, DPS, Device Twins, routing, tiers |
| 📊 07 — Feature Comparison | Side-by-side tables: ETL vs streaming, SQL options, analytics layers |
| 🎯 08 — Exam Caveats & Cheatsheet | Decision trees, exam traps, quick-fire numbers, final checklist |
🔑 Why Data & Analytics Matters for AZ-305
Data services surface across all four exam domains:
- Domain 2 — Data Storage Solutions (25–30%): Choosing between Azure SQL options; relational vs NoSQL; data warehouse vs data lake
- Domain 4 — Infrastructure Solutions (30–35%): IoT architecture, stream processing pipelines, analytics platform design
- Business Continuity: SQL Geo-replication, Synapse failover, IoT Hub failover
- Well-Architected Framework: Cost optimisation between Synapse serverless vs dedicated; right-sizing Databricks clusters
⚠️ The exam frequently presents architecture scenarios where multiple services overlap — knowing exactly when to use Stream Analytics vs Databricks vs Synapse, or SQL Database vs Managed Instance vs SQL on VM, is where marks are won or lost.
⚡ Quick Navigation
| I need to know… | Go to |
|---|---|
| SQL Database vs Managed Instance vs VM | 07 — Comparison § SQL Options |
| ADF vs Synapse Pipelines vs Databricks for ETL | 07 — Comparison § ETL |
| Stream Analytics vs Event Hubs vs Databricks Streaming | 07 — Comparison § Streaming |
| IoT Hub vs IoT Central vs Event Hubs | 07 — Comparison § IoT |
| All exam traps in one place | 08 — Exam Caveats |
| Azure SQL HA & SLA options | 01 — Azure SQL § High Availability |
| Synapse Dedicated vs Serverless SQL pools | 04 — Synapse § SQL Pools |
©️ Credits & Acknowledgements
The Just the Docs theme is used for a clean, documentation-style layout. Licensed under MIT.
Created with the help of AI. Model used: Claude Sonnet 4.6. The content has been reviewed and edited by the author for accuracy and clarity, but may contain errors. Always verify against the latest Microsoft documentation.
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