An independent study guide for Microsoft Certified: Azure Data Fundamentals · by Tony Rough
Know which data store, analytics service and report fits the job, and why.
Publishing soon on Amazon in Kindle and paperback editions.
This independent study guide for the Microsoft Certified: Azure Data Fundamentals exam distils what DP-900 really expects you to understand into clear definitions, comparisons and the traps that catch newcomers. It assumes no previous experience with data or with Azure and is written to the skills measured as of July 2026.
Nine chapters, each readable on its own and together covering all four DP-900 skill areas:
Azure's data services change quickly. This edition reflects Microsoft's documentation as of October 2026, including Microsoft Fabric and Azure Databricks as the large-scale analytics platforms, Fabric Real-Time Intelligence for streaming, and the retirement of older database deployment options.
This book contains no exam questions. It explains the knowledge the exam expects, so you can answer questions you have never seen and carry the same understanding into real data work on Azure.
Written by Tony Rough, a cloud architect with more than twenty years in IT infrastructure who holds the Azure Solutions Architect Expert, Azure Administrator and Azure Security Engineer certifications.
Part of the Ultra Transcenders series from Distilled Press. An independent publication, not affiliated with, sponsored by or endorsed by Microsoft Corporation.
Every skill area in Microsoft's DP-900 outline (as of July 21, 2026), and the chapters that cover it.
| Skill area | Weight | Chapters |
|---|---|---|
| Describe core data concepts | 25–30% | 1, 2 |
| Identify considerations for relational data on Azure | 20–25% | 3, 4 |
| Describe considerations for working with non-relational data on Azure | 15–20% | 5, 6 |
| Describe an analytics workload | 25–30% | 7, 8, 9 |
Plus an appendix glossary of 200+ terms, each linked to Microsoft Learn, with the same terms explained free online for print readers.
Some sections of the book, free to read online:
What each ACID property guarantees in a transactional (OLTP) database, with the classic funds-transfer example.
How extract-transform-load and extract-load-transform differ, and why ELT is common in modern lakehouses.
How OLTP and analytical systems differ in purpose, data shape, queries and users.
How normalisation splits data into one table per entity, linked by keys, so each fact is stored once.
The three Azure SQL options side by side: IaaS or PaaS, compatibility, management and availability.
Which Azure SQL option or open-source database service fits a requirement, and why.
Storage and access costs, minimum retention periods, Archive rehydration and lifecycle management policies.
The key characteristics of Azure Cosmos DB: schema-agnostic items, automatic indexing, global distribution and low latency.