Microsoft DP-900 Deutsch Q&A - in .pdf

  • Exam Code: DP-900 Deutsch
  • Exam Name: Microsoft Azure Data Fundamentals (DP-900 Deutsch Version)
  • Q & A: 320 Questions and Answers
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About Microsoft Azure Data Fundamentals (DP-900 Deutsch Version) - DP-900 Deutsch Exam

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How to Register For Exam DP-900: Microsoft Azure Data Fundamentals?

Exam Register Link: https://examregistration.microsoft.com/?locale=en-us&examcode=DP-900&examname=Exam%20DP-900:%20Microsoft%20Azure%20Data%20Fundamentals&returnToLearningUrl=https%3A%2F%2Fdocs.microsoft.com%2Flearn%2Fcertifications%2Fexams%2Fdp-900

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

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:

  • ‘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.
  • ‘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.

The Microsoft DP-900 exam is intended for candidates who already have foundational knowledge and skills in performing basic tasks and using Microsoft Azure data services. It is also recommended for those who are starting their careers in the field of cloud data. Although there are no strict prerequisites, every individual who desires to take DP-900 test should have familiarity with non-relational and relational data as well as various types of data workloads such as analytical and transactional.

Compiled by professional experts

We invited a group of professional experts to preside over the contents of the test in so many years. They are so familiar with the test that can help exam candidates effectively pass the exam without any difficulty. To clear your confusion about the difficult points, they give special explanations under the necessary questions. All knowledge of the Microsoft Microsoft Azure Data Fundamentals (DP-900 Deutsch Version) exam study torrent is unequivocal with concise layout for your convenience. Their wariness and profession are far more than you can imagine. And they are practiced experts dedicated to Microsoft Microsoft Azure Data Fundamentals (DP-900 Deutsch Version) valid exam dumps in this area over 10 years who can totally be trusted.

Microsoft DP-900 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Identify considerations for relational data on Azure20–25%- Describe relational data concepts
  • 1. Query data with SQL
    • 2. Relationships, keys, constraints
      • 3. Normalization
        - Describe Azure relational data services
        • 1. Open-source databases: PostgreSQL, MySQL, MariaDB
          • 2. SQL Server on Azure Virtual Machines
            • 3. Azure SQL Database
              • 4. Azure SQL Managed Instance
                Describe considerations for working with non-relational data on Azure15–20%- Describe Azure Cosmos DB
                • 1. Capabilities and features
                  • 2. Consistency levels and partitioning
                    • 3. APIs and data models
                      - Describe non-relational data concepts
                      • 1. Use cases for non-relational data
                        • 2. Characteristics of NoSQL data
                          - Describe Azure storage services
                          • 1. Blob Storage
                            • 2. Queue Storage
                              • 3. File Storage
                                • 4. Table Storage
                                  Describe an analytics workload on Azure25–30%- Describe Azure analytics services
                                  • 1. Azure Synapse Analytics
                                    • 2. Azure HDInsight
                                      • 3. Azure Databricks
                                        • 4. Azure Data Lake Storage Gen2
                                          • 5. Microsoft Fabric
                                            - Describe real-time analytics
                                            • 1. Azure Stream Analytics
                                              • 2. Stream processing concepts
                                                - Describe data visualization
                                                • 1. Data models and reports
                                                  • 2. Power BI capabilities
                                                    - Describe big data and analytics concepts
                                                    • 1. Data lakes and data warehouses
                                                      • 2. Modern data warehouse architecture
                                                        • 3. Data ingestion and processing
                                                          Describe core data concepts25–30%- Describe types of data
                                                          • 1. File formats
                                                            • 2. Structured, semi-structured, and unstructured data
                                                              - Describe data workloads
                                                              • 1. Transactional workloads
                                                                • 2. Analytical workloads
                                                                  • 3. Batch and streaming data
                                                                    - Describe roles and responsibilities
                                                                    • 1. Data engineer, data analyst, database administrator

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