Microsoft DP-900 Korean : Microsoft Azure Data Fundamentals (DP-900 Korean Version)

  • Exam Code: DP-900 Korean
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Korean Version)
  • Updated: Aug 06, 2026   Q&As: 320 Questions and Answers

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Helpful Books to Ace DP-900

By and large, candidates can incorporate the listed study guides from Amazon as they prepare for DP-900 so they have a better chance of passing the official test:

  • ‘DP-900: Microsoft Azure Data Fundamentals 2020 Practice Exam (Solved Practice Test 120+)’ by Eaze Teach — Eaze Teach is one of the largest online IT content providers in the world and they have study guides & mock tests for technical exams of numerous IT vendors such as Linux, Cisco, and Microsoft. Plus, Eaze Teach even provides training courses to IT workers to succeed in their job positions. This almost 150-page paperback from such a provider is loaded with practice tests consisting of 120+ original and challenging questions for the Microsoft exam DP-900. These practice tests are meant to exactly replicate the actual DP-900 test, hence the structure, question types, time limit, and passing score are the same as DP-900. Significantly, each question in this book has been created in accordance with the official exam syllabus issued by Microsoft for DP-900, meaning they’ll cover all the necessary topics. Taking the mock tests in this book is a great way to assess where the candidate currently stands in terms of exam preparation and advance accordingly. Furthermore, these mocks will also help candidates identify gaps in their knowledge.
  • ‘Exam Ref DP-900 Microsoft Azure Data Fundamentals’ by Daniel Seara & Francesco Milano — this is the official paperback provided by Microsoft for DP-900 test. Both the authors of this book are experienced IT veterans who have spent decades working with countless technologies. The target audience for this book is IT professionals, functional consultants, and business users. Simply put, it focuses on the main concepts and skills one would need in order to provide data solutions using Microsoft Azure data services out in the real world. Plus, such material promotes critical thinking in learners so they will be able to make better decisions on the job. More so, this book comprehensively covers each and every topic that candidates need to know for their DP-900 tests. This official paperback is also packed with ‘what if’ questions to further challenge the learners and teach them how to solve real-world IT problems. To easily blaze through the pages of this revision guide, candidates must be familiar with working with cloud-related data, Microsoft Azure data services, and know all the basic data concepts.
  • ‘DP-900: Microsoft Azure Data Fundamentals: 110+ Exam Practice Questions with Detail Explanation and Reference Link’ by Analytiq Tech and Daniel Scott — this kindle guide contains more than 110 original and challenging sample questions for DP-900. What’s more is that each question is accompanied by detailed answers, which help students grasp why an answer is correct or incorrect, hence they can improve faster. In all, there are two entire mock tests in this e-book and the question type, time limit, structure, and passing score of those mock tests will exactly replicate that of DP-900, meaning students will receive the perfect practice. Taking mock tests such as these helps students assess their performance and identify the topics they are weak in. The question bank of this book is being constantly updated and improved using students’ feedback, and new items are added to the stock on a regular basis. The book even has an active Q&A forum online, where past and future candidates discuss the exam topics of DP-900 and share their test-taking experiences, all of which should facilitate further learning for potential candidates.

How to operate with relational data on Azure

Here, the candidate should be equipped with knowledge and skills in the following sub domains:

  • Relational Azure data services – this section of the exam is focused on the following: the understanding of IaaS, SaaS and PaaS solutions and their comparison, Azure SQL DB services such as Azure SQL managed instance and Azure virtual machine, Azure Synapse Analytics, and Azure Database for MariaDB, PostgreSQL and for MySQL.
  • Data querying techniques that require utilizing SQL language – it deals with the Data Manipulation Language (DML) and Data Definition Language (DDL) as well as querying relational data on Azure SQL DB.
  • Identification of basic management roles for relational data – under this sub domain there are several skills covered that include the deployment and provisioning of relational data, various deployment methods such as Azure Resource Manager templates, Azure portal, Azure command-line interface (CLI), etc. Also, one should be knowledgeable in data components identification (authentication and firewall), the identification of basic connectivity problems such as accessing Azure VNets, firewalls, access from the internet and authentication). One more knowledge area involved is query tools (SQL Management Studio, Azure Data Studio, utility, sqlcmd etc.).
  • Relational data workloads – the candidate has to gain skills in identifying the appropriate data offerings when it comes to relational workload and learn more about structures of relational data.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900

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Microsoft DP-900 Exam Syllabus Topics:

TopicDetails

Describe core data concepts (15-20%)

Describe types of core data workloads- describe batch data
- describe streaming data
- describe the difference between batch and streaming data
- describe the characteristics of relational data
Describe data analytics core concepts- describe data visualization (e.g., visualization, reporting, business intelligence (BI))
- describe basic chart types such as bar charts and pie charts
- describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive)
- describe ELT and ETL processing
- describe the concepts of data processing

Describe how to work with relational data on Azure (25-30%)

Describe relational data workloads- identify the right data offering for a relational workload
- describe relational data structures (e.g., tables, index, views)
Describe relational Azure data services- describe and compare PaaS, IaaS, and SaaS solutions
- describe Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machines
- describe Azure Synapse Analytics
- describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL
Identify basic management tasks for relational data- describe provisioning and deployment of relational data services
- describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)
- identify data security components (e.g., firewall, authentication)
- identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)
- identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.)
Describe query techniques for data using SQL language- compare Data Definition Language (DDL) versus Data Manipulation Language (DML)
- query relational data in Azure SQL Database, Azure Database for PostgreSQL, and Azure Database for MySQL

Describe how to work with non-relational data on Azure (25-30%)

Describe non-relational data workloads- describe the characteristics of non-relational data
- describe the types of non-relational and NoSQL data
- recommend the correct data store
- determine when to use non-relational data
Describe non-relational data offerings on Azure- identify Azure data services for non-relational workloads
- describe Azure Cosmos DB APIs
- describe Azure Table storage
- describe Azure Blob storage
- describe Azure File storage
Identify basic management tasks for non-relational data- describe provisioning and deployment of non-relational data services
- describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)
- identify data security components (e.g., firewall, authentication, encryption)
- identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)
- identify management tools for non-relational data

Describe an analytics workload on Azure (25-30%)

Describe analytics workloads- describe transactional workloads
- describe the difference between a transactional and an analytics workload
- describe the difference between batch and real time
- describe data warehousing workloads
- determine when a data warehouse solution is needed
Describe the components of a modern data warehouse- describe Azure data services for modern data warehousing such as Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight
- describe modern data warehousing architecture and workload
Describe data ingestion and processing on Azure- describe common practices for data loading
- describe the components of Azure Data Factory (e.g., pipeline, activities, etc.)
- describe data processing options (e.g., Azure HDInsight, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)
Describe data visualization in Microsoft Power BI- describe the role of paginated reporting
- describe the role of interactive reports
- describe the role of dashboards
- describe the workflow in Power BI

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