Entry point to data on Azure and the DP-900 certification
DP-900 is a one-day introductory training course that provides a structured overview of data concepts and their associated Microsoft Azure services.
You will cover the foundations of the data domain: data types (structured, semi-structured, unstructured), transactional and analytical workloads, and batch vs. stream processing. You will then discover how Azure organizes its data services into three major categories:
• Relational (Azure SQL family, managed open-source databases),
• Non-relational (Azure storage, Cosmos DB),
• Analytical (Microsoft Fabric, Azure Databricks, Power BI).
The training is aimed at a wide range of professionals working with data: analysts, business intelligence (BI) teams, developers, solution architects, or IT professionals involved in data migration or transformation projects to the cloud.
It prepares you for the DP-900 certification exam: Microsoft Azure Data Fundamentals and serves as a solid entry point before more advanced training in data engineering, analytics, or database administration on Azure.
Is it for you ?
DP-900 is aimed at diverse profiles working with data or involved in data transformation projects, without necessarily being the primary architects or engineers.
It is particularly suitable for:
• Data analysts and business intelligence (BI) team members who want to understand the Azure services that support their tools and data sources.
• Developers and solution architects who want to structure their conceptual knowledge of data in an Azure context before tackling more advanced training.
• IT professionals involved in cloud data migration or modernization projects.
• Project managers and business stakeholders driving data initiatives who wish to better understand the Azure ecosystem.
• Anyone preparing for the DP-900 certification exam: Microsoft Azure Data Fundamentals.
Prerequisites
No mandatory prerequisites.
General familiarity with basic IT concepts (files, tables, databases) facilitates the understanding of examples, but is not required to take the course.
What You'll Walk Away With
- ✓ Distinguish between data types and workloads: structured, semi-structured, and unstructured data, transactional vs. analytical, batch vs. stream processing.
- ✓ Identify Azure relational data services suited to your context: Azure SQL family, managed open-source databases, and SQL on virtual machines.
- ✓ Locate non-relational data options on Azure: Blob storage, Tables, and Azure Cosmos DB, along with their respective use cases.
- ✓ Understand the components of an analytical pipeline on Azure, from data storage and ingestion to visualization with Power BI.
- ✓ Assess your readiness for the DP-900 exam through the end-of-day quiz, guided correction, and targeted revision paths.
Training content
DP-900 alternates between structured presentations, guided demonstrations in Azure services, and contextual scenarios and quizzes. There are no practical labs in this format: the objective is to understand and contextualize data concepts and services, not yet to deploy them. The day concludes with a DP-900 exam-style quiz with guided correction.
1 Distinguishing data types and roles in a data project
The fundamental concepts that structure the world of data, before addressing Azure services.
- Structured, semi-structured, and unstructured data: definitions, common formats, and concrete examples
- Database types: relational, non-relational, analytical
- Roles in a data project: data engineer, analyst, data scientist, database administrator
2 Understanding data workloads: transactional and analytical
Two major families of workloads that address distinct needs and rely on different services.
- Transactional workloads (OLTP): characteristics, use cases, and requirements
- Analytical workloads (OLAP): characteristics, use cases, and differences from transactional workloads
- Batch processing and streaming: introduction to the two approaches
3 Exploring relational data services on Azure
Azure services for managing and querying relational data, from managed SQL databases to open-source engines.
- Basic SQL concepts: tables, keys, relationships, and queries
- Azure SQL family: Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Virtual Machines
- Managed open-source relational databases on Azure: MySQL, PostgreSQL, MariaDB
- Positioning each service according to migration or deployment scenarios
4 Discovering non-relational data options on Azure
Azure services for data that does not fit into a classic relational model.
- Azure storage for unstructured data: Blob, Files, and Tables
- Azure Cosmos DB: distributed NoSQL database, use cases, and main available APIs
- Criteria for choosing between non-relational options based on data type and workload
5 Understanding data analytics and validating learning
The components of a data analysis solution on Azure, from sources to dashboards, followed by a wrap-up of the day.
- Data ingestion and processing: the role of each step in an analytical pipeline
- Azure analytical options: Microsoft Fabric and Azure Databricks (positioning concepts)
- Visualization with Microsoft Power BI: connecting to sources, dashboards, and reports
- Timed DP-900 exam-style quiz with guided correction and revision paths
Keep in Mind
Exam assessment and preparation Final quiz (25–40 questions) + guided correction
📌 Practical information
Our training sessions are available as private sessions, delivered in person at your premises, in a virtual format, or in our training rooms according to your needs.
Dates, schedules, language of instruction, and formats are fully customizable for your team.
To schedule a training session or request a proposal, please fill out the request form below and our team will get back to you shortly.