Microsoft Azure Data Fundamentals Exam Guide (DP-900)

Overview

This course provides a clear path to mastering Azure data fundamentals and preparing for the DP-900 certification exam. It covers key concepts such as structured, semi-structured, and unstructured data, along with essential Azure services, ensuring learners build a strong foundation in cloud data solutions. Learners will gain the knowledge and skills required to analyze data features, utilize Azure SQL and open-source database services, and evaluate various Azure storage options. The practical examples provided will help boost confidence and prepare you for success in the DP-900 exam. The course is unique because it combines clear theoretical explanations with practical real-world applications, offering a comprehensive understanding of Azure data services that aligns with exam requirements. This course is ideal for administrators, engineers, analysts, or anyone interested in data careers, provided they have a basic understanding of cloud concepts and client-server applications. Based on the book, Microsoft Azure Data Fundamentals (DP-900) Exam Guide, by Steve Miles.

Syllabus

Describe Core Data Concepts

In this section, we explore core data concepts, including data representation, storage options, and roles in data workloads, providing foundational knowledge for data-driven decision-making.

Describe Relational Concepts

In this section, we explore relational data concepts, normalization, SQL statements, and database objects to build foundational knowledge for efficient data management and the DP-900 Azure certification.

Describe Relational Azure Data Services

In this section, we explore Azure relational data services, focusing on Microsoft and open source databases, deployment methods, and exam readiness for DP-900.

Describe the Capabilities of Azure Storage

In this section, we explore Azure Storage capabilities, including Blob, Files, and Table storage, for managing structured, semi-structured, and unstructured data in cloud environments.

Describe the Capabilities and Features of Azure Cosmos DB

In this section, we explore Azure Cosmos DB's capabilities, use cases, and APIs, emphasizing its multi-model, scalable, and flexible design for diverse application needs.

Common Elements of Large-Scale Analytics

In this section, we explore large-scale analytics architecture, focusing on data ingestion, storage, and Azure services like Synapse Analytics and Databricks for efficient data management and analysis.

Describe Consideration for Real-Time Data Analytics

In this section, we explore batch and streaming data processing methods and identify Azure services for real-time analytics, focusing on practical applications and decision-making.

Describe Data Visualization in Microsoft BI

In this section, we explore Power BI's data visualization capabilities, focusing on interactive reports, dashboards, and data modeling to enhance decision-making and exam readiness.