📖 About this Domain
This domain introduces foundational data concepts, including data formats and processing types. It establishes the core terminology for relational, non-relational, and analytical data workloads.
🎓 What You Will Learn
- Differentiate between transactional workloads (OLTP) and analytical workloads (OLAP).
- Identify the responsibilities for data roles like database administrator, data engineer, and data analyst.
- Describe relational data concepts including tables, normalization, and structured query language (SQL).
- Describe non-relational data concepts including NoSQL databases and types like key-value, document, and graph.
🛠️ Skills You Will Build
- Ability to classify data as structured, semi-structured, or unstructured.
- Skill to differentiate between batch data and streaming data processing.
- Competency in describing relational database constructs like tables, indexes, and views.
- Skill to identify appropriate use cases for non-relational NoSQL data stores.
💡 Top Tips to Prepare
- Focus on the characteristics of OLTP versus OLAP systems, as this is a fundamental concept.
- Memorize the specific duties of the three core data roles: administrator, engineer, and analyst.
- Understand the concept of normalization and why it is used in relational databases.
- Practice matching data types like JSON or CSV to semi-structured data definitions.
📖 About this Domain
This domain covers the fundamentals of non-relational data, also known as NoSQL data, on the Azure platform. It focuses on the core characteristics of non-relational data stores and introduces the primary Azure services used to manage them. You will explore services like Azure Storage and Azure Cosmos DB.
🎓 What You Will Learn
- Describe the characteristics and types of non-relational data, including key-value, document, columnar, and graph models.
- Explore the capabilities of Azure Blob, Azure File, and Azure Table storage for managing unstructured and semi-structured data.
- Understand the core concepts of Azure Cosmos DB, including its global distribution, multi-model APIs, and consistency levels.
- Identify the basic provisioning and configuration options for non-relational data services in the Azure portal.
🛠️ Skills You Will Build
- Ability to differentiate between relational and non-relational data workloads.
- Skill in selecting the appropriate Azure Storage service (Blob, File, Table) for a given data scenario.
- Competence in identifying the correct Azure Cosmos DB API (e.g., Core SQL, Gremlin, MongoDB) for specific application needs.
- Capability to describe the process of provisioning a basic Azure Cosmos DB account and an Azure Storage account.
💡 Top Tips to Prepare
- Focus on the specific use cases for each Azure Cosmos DB API, as this is a common topic for exam questions.
- Memorize the differences between Azure Blob Storage access tiers (Hot, Cool, Archive) and their cost and latency implications.
- Create a clear mental model distinguishing the purpose of Azure Blob, Azure File, and Azure Table storage.
- Utilize the Microsoft Learn sandboxes or an Azure free account to practice creating and configuring these non-relational data services.
📖 About this Domain
This domain covers key concepts related to 2: Describe how to work with relational data on Azure.
🎓 What You Will Learn
- Core concepts of 2: Describe how to work with relational data on Azure
- Best practices and implementation
- Real-world application scenarios
🛠️ Skills You Will Build
- Technical proficiency in 2: Describe how to work with relational data on Azure
- Problem-solving abilities
- Practical implementation skills
💡 Top Tips to Prepare
- Review official documentation and study guides
- Practice with hands-on exercises
- Focus on understanding core principles
📖 About this Domain
This domain covers the fundamentals of data analytics workloads on Azure. You will explore the differences between transactional (OLTP) and analytical (OLAP) systems. It introduces core Azure services for data warehousing, big data processing, and real-time analytics.
🎓 What You Will Learn
- Understand the core components of a modern data warehouse, including data ingestion and ETL/ELT processes.
- Identify the features and use cases for Azure Synapse Analytics, Azure Databricks, and Azure HDInsight.
- Learn about real-time data streaming and analytics using services like Azure Stream Analytics.
- Explore data visualization concepts and the role of Microsoft Power BI for creating reports and dashboards.
🛠️ Skills You Will Build
- Ability to differentiate between transactional (OLTP) and analytical (OLAP) data processing workloads.
- Skill to identify appropriate Azure services for batch and real-time data analytics scenarios.
- Competency in describing the architecture of a modern data warehouse on Azure.
- Understanding of how to use Power BI for business intelligence and data visualization.
💡 Top Tips to Prepare
- Focus on the high-level purpose of Azure Synapse Analytics, Azure Databricks, and Azure HDInsight, not their deep implementation details.
- Memorize the key differences between batch processing and stream processing and which Azure services support each.
- Understand the core concepts of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) pipelines.
- Review the main components of a Power BI report, such as dashboards, visuals, and datasets.
