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How to operate with relational data on Azure

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

  • 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.
  • 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.

Exam DP-900: Microsoft Azure Data Fundamentals

Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.

This exam is intended for candidates beginning to work with data in the cloud.

Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.

Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure Data Fundamentals

Download exam skills outline

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

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Microsoft DP-900 Deutsch Exam Syllabus Topics:

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

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