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Explain the Techniques Involved in Working with Relational Data on Microsoft Azure: 25-30%
- Explain Relational Azure Data Services: The individuals should have the ability to explain and compare SaaS, PaaS, and IaaS solutions as well as Azure Synapse Analytics. They also need the knowledge of Azure SQL database services, Azure Database for PostgreSQL, Azure Database for MySQL, and Azure Database for MariaDB.
- Explain the Query Methods for Data with the SQL Language: The learners should be capable of comparing the Data Manipulation Language with the Data Definition Language. They should also be able to query relational data within Azure Database for MySQL, Azure SQL Database, and Azure Database for PostgreSQL.
- Explain the Concepts of Relational Data Workloads: The examinees should be able to explain the structures of relational data and identify the appropriate data for relational workloads.
- Identify the Fundamental Management Tasks for Relational Data: The applicants should be able to explain the deployment and provisioning of relational data services. They also need to understand the techniques for deployment, such as Azure Resource Manager templates, Azure portal, Azure CLI, and Azure PowerShell. In addition, the students should be able to identify the fundamental connectivity issues and components of data security.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-900
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Certification Paths Available
Upon earning Microsoft Certified: Azure Data Fundamentals, you will be able to advance your career to higher-level certifications. For instance, it can be a starting point for Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Azure Database Administrator Associate. However, this fundamental accreditation is not a requirement for earning any of the next certificates. Therefore, all you have to do is to pass Microsoft DP-900 exam and prepare to face the real-world challenges as you advance in your career.
Microsoft DP-900 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics Workloads in Azure | 25-30% | - Azure analytics services
- Data ingestion and processing - Data visualization and reporting |
| Topic 2: Relational Data in Azure | 20-25% | - Querying relational data - Azure relational data services
|
| Topic 3: Non-Relational Data in Azure | 15-20% | - Non-relational data concepts - Azure storage services
|
| Topic 4: Core Data Concepts | 25-30% | - Relational vs non-relational data - Roles and responsibilities in data work - Data analytics workloads overview - Types of core data workloads |

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