DP-900 Microsoft Azure Data Fundamentals Practice Tests

DP-900 Microsoft Azure Data Fundamentals Practice Tests free download

Master and Pass the DP-900: Azure Data Fundamentals examination with 5 vetted and verified practice test questions.

PASSING the DP-900: Azure Data Fundamentals examination will demonstrate your subject matter expertise to your current and future employers. Azure is one the most popular and widely used commercial clouds in the world, and data is becoming a businesses most valuable asset. Understanding the core Azure data services, storage mechanisms, security suite, and core technologies will separate your resume from the rest. This certification can potentially land you a high-paying job in the cloud & tech industry. The cloud is the future, and your career growth and earning potential starts here with DP-900: Azure Data Fundamentals.

Our Azure Data Fundamentals practice test questions are based off the official DP-900: Azure Data Fundamentals Study Guide, and various associated azure data services documentations available online. Additionally, our questions were verified and validated by certified Azure cloud engineers. And to make it even better, we provided detailed explanations to each question, so you can truly master the concepts, understand why the answer is correct, and most importantly, why the other answer choices are wrong.

We designed our practice tests to mimic the real exam. Our questions are asked the exact same way as the real exam, and they come with detailed explanations, diagrams, and valuable reference links to help you learn. Our practice tests will be the final step of your preparation. Please trust us, we spent hours curating these questions. We will be with you every step of the way.

Our only question is this - are you ready? Let's get you certified right now.

The DP-900: Azure Data Fundamentals examination will test you on these key skills:

(1.) Describe core data concepts (25–30%)

Describe ways to represent data

• Describe features of structured data

• Describe features of semi-structured

• Describe features of unstructured data

Identify options for data storage

• Describe common formats for data files

• Describe types of databases

Describe common data workloads

• Describe features of transactional workloads

• Describe features of analytical workloads

Identify roles and responsibilities for data workloads

• Describe responsibilities for database administrators

• Describe responsibilities for data engineers

• Describe responsibilities for data analysts

(2.) Identify considerations for relational data on Azure (20–25%)

Describe relational concepts

• Identify features of relational data

• Describe normalization and why it is used

• Identify common structured query language (SQL) statements

• Identify common database objects

Describe relational Azure data services

• Describe the Azure SQL family of products including Azure SQL Database, Azure SQL

• Managed Instance, and SQL Server on Azure Virtual Machines

• Identify Azure database services for open-source database systems

(3.) Describe considerations for working with non-relational data on Azure (15–20%)

Describe capabilities of Azure storage

• Describe Azure Blob storage

• Describe Azure File storage

• Describe Azure Table storage

Describe capabilities and features of Azure Cosmos DB

• Identify use cases for Azure Cosmos DB

• Describe Azure Cosmos DB APIs

(4.) Describe an analytics workload on Azure (25–30%)

Describe common elements of large-scale analytics

• Describe considerations for data ingestion and processing

• Describe options for analytical data stores

• Describe Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Azure HDInsight, and Azure Data Factory

Describe consideration for real-time data analytics

• Describe the difference between batch and streaming data

• Describe technologies for real-time analytics including Azure Stream Analytics, Azure Synapse Data Explorer, and Spark Structured Streaming

Describe data visualization in Microsoft Power BI

• Identify capabilities of Power BI

• Describe features of data models in Power BI

• Identify appropriate visualizations for data