As businesses worldwide shift towards cloud computing, mastering cloud-based data services has become essential for IT professionals. One of the foundational certifications to build expertise in this area is the Microsoft DP-900: Azure Data Fundamentals exam. This certification is an entry-level credential designed to validate your knowledge of core data concepts and how they are implemented using Microsoft Azure services.
In this article, we will provide a detailed guide to the DP-900 exam, covering key topics, preparation tips, and strategies to help you pass the exam and establish a solid foundation in data and cloud technologies.
1. What Is the Microsoft DP-900 Exam?
The DP-900 certification focuses on Azure Data Fundamentals and is perfect for individuals starting their journey in data-related roles. The exam is designed to assess your understanding of fundamental data concepts such as relational and non-relational data, analytics workloads, and how these concepts are implemented using Microsoft Azure data services. This certification can serve as a launching pad for other Azure certifications, such as the Azure Data Engineer or Azure Database Administrator certifications.Key Exam Details:
- Number of questions: 40-60 questions
- Question types: Multiple-choice, drag-and-drop, and scenario-based
- Duration: 60 minutes
- Passing score: 700 out of 1000
- Cost: $99 (regional pricing may vary)
- Prerequisites: No prerequisites, though a basic understanding of cloud computing and databases is recommended.
2. Key Areas Covered in the DP-900 Exam
The DP-900 exam is structured around key data concepts and how they are implemented in Azure. The exam blueprint is divided into four main sections, each representing a key knowledge area.a. Core Data Concepts (15-20%)
This section tests your basic understanding of data and its various formats. The topics covered include:- Understanding the difference between structured, semi-structured, and unstructured data
- Core data concepts such as transactions, consistency, and indexing
- How databases work (including relational and non-relational models)
b. Relational Data in Azure (25-30%)
Relational databases have been a core part of data management for decades, and Azure offers several solutions in this space. In this section, you’ll need to demonstrate knowledge of:- Relational databases and SQL
- Azure SQL Database and Azure Database for PostgreSQL
- Key concepts like tables, primary keys, foreign keys, and relationships
- How to provision, configure, and scale relational database services in Azure
c. Non-Relational Data in Azure (25-30%)
As organizations increasingly turn to non-relational databases to handle large-scale, diverse datasets, this section focuses on understanding non-relational databases and their uses in Azure:- Non-relational data models such as key-value stores, document databases, and graph databases
- Azure Cosmos DB and its multiple APIs (e.g., Core (SQL), MongoDB, Cassandra, Gremlin)
- How to deploy, manage, and scale non-relational databases in Azure
d. Analytics Workloads on Azure (25-30%)
Data analytics is crucial for deriving insights from vast amounts of data. In this section, the focus shifts to using Azure services to analyze data:- Key concepts in data analytics, such as data ingestion, transformation, and visualization
- Azure Synapse Analytics, Azure HDInsight, and Azure Databricks
- Basics of big data, data lakes, and data warehousing
- Power BI and its role in data visualization and reporting