Microsoft DP-900 Exam Syllabus & Study Guide

At Certs4Success, we provide the most accurate and up-to-date preparation materials for the Microsoft DP-900 Exam. Our content is professionally designed to help you master all the essential topics required to pass the Microsoft DP-900 Exam with confidence and build a strong foundation in data concepts and cloud data services. If you are planning to clear the Microsoft DP-900 Exam, this detailed syllabus will guide you through all the important domains you need to focus on.

All Exam Topics of Microsoft DP-900 Exam

Topic 1: Core Data Concepts

Data Types: Understanding structured, semi-structured, and unstructured data.
Data Workloads: Exploring transactional (OLTP) and analytical (OLAP) workloads.
Data Roles: Understanding responsibilities of data engineers, analysts, and scientists.
Data Processing: Batch vs real-time data processing concepts.

Topic 2: Relational Data in Azure

Relational Databases: Understanding relational database concepts and SQL fundamentals.
Azure SQL Solutions: Working with relational services in Microsoft Azure ecosystem such as Azure SQL Database.
Querying Data: Using SQL to retrieve and manipulate structured data.
Data Normalization: Understanding database design principles.

Topic 3: Non-Relational Data in Azure

NoSQL Databases: Understanding key-value, document, and graph data stores.
Azure Cosmos DB: Working with globally distributed NoSQL databases.
Table Storage: Using Azure Table Storage for simple data models.
Data Modeling: Choosing appropriate storage for different data types.

Topic 4: Analytics Workloads in Azure

Data Warehousing: Understanding modern data warehouse concepts.
Azure Synapse Analytics: Exploring integrated analytics services.
Big Data Processing: Handling large-scale data workloads.
Data Pipelines: Moving and transforming data efficiently.

Topic 5: Data Storage & Data Services

Storage Options: Understanding blob, file, and disk storage.
Data Lake Concepts: Working with large-scale data lakes.
Azure Data Lake: Managing big data storage in Microsoft Azure.
Data Security: Ensuring secure storage and access control.

Topic 6: Data Processing & Analytics Tools

ETL Processes: Extract, transform, and load operations.
Data Integration: Using Azure Data Factory for pipelines.
Stream Processing: Handling real-time data ingestion.
Data Transformation: Preparing data for analytics and reporting.

Topic 7: Data Visualization & Reporting

Power BI Basics: Creating dashboards and reports.
Data Visualization: Understanding charts, graphs, and KPIs.
Business Insights: Turning raw data into actionable insights.
Report Sharing: Collaborating across teams using reports.

Topic 8: Security, Compliance & Governance

Data Security: Protecting sensitive information in cloud environments.
Access Control: Role-based access control (RBAC) in Azure.
Data Encryption: Securing data at rest and in transit.
Compliance Standards: Understanding regulatory requirements and governance.

Topic 9: Modern Data Architecture

Cloud Data Platforms: Overview of modern cloud-based architectures.
Hybrid Data Solutions: Integrating on-premises and cloud systems.
Scalability: Designing scalable data solutions.
Performance Optimization: Improving query and storage performance.

Topic 10: Monitoring & Maintenance

Monitoring Tools: Tracking performance and usage in Azure.
Data Quality: Ensuring accuracy and consistency of data.
Troubleshooting: Identifying and resolving data issues.
Cost Management: Optimizing data storage and processing costs.

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