IL - DP-900: Microsoft Azure Data Fundamentals
In this course you will learn about data concepts. You will also learn how to work with both relational and non-relational data on Azure. We will also cover analytics workload on Azure in this module as well. This course will help prepare you to pass the Microsoft certification exam DP-900: Microsoft Azure Data Fundamentals.
- Duration: 1 day
- Level: 100
Who this course is designed for
- Data Engineer
- Database Administrator
- Describe core data concepts in Azure
- Explain concepts of relational data in Azure
- Explain concepts of non-relational data in Azure
- Identify components of a modern data warehouse in Azure
Module 01 – Types of Core Data Workloads
In this module you will learn about batch data, streaming data, the difference between batch and streaming data and the characteristics of relational data.
Module 02 - Data Analytics Core Concepts
This module will cover data visualization (e.g., visualization, reporting, business intelligence), basic chart types such as bar charts and pie charts and analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive). You will also learn about ELT and ETL processing and the concepts of data processing.
Module 03 - Relational Data Workloads
In this module you will learn how to identify the right data offering for a relational workload as well as relational data structures (e.g., tables, index, views).
Module 4 - Relational Azure Data Services
In this module you will learn how to describe and compare PaaS, IaaS, and SaaS delivery models, describe Azure SQL Database, Azure Synapse Analytics and SQL Server on Azure Virtual Machine. You will also learn about Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL and Azure SQL Managed Instance.
Module 05 - Basic Management Tasks for Relational Data
In this module you will learn about provisioning and deployment of relational data services, methods for deployment including ARM templates and Azure Portal and how to identify data security components (e.g., firewall, authentication). This module will also cover how to identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) and query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.).
Module 06 - Query Techniques for Data Using SQL Language
In this module you will learn how to compare DDL versus DML and query relational data in PostgreSQL, MySQL, and Azure SQL Database.
Module 07 - Non-Relational Data Workloads
In this module you will learn about the characteristics of non-relational data and the types of non-relational and NoSQL data. This module will also cover how to recommend the correct data store and determine when to use non-relational data.
Module 08 - Non-Relational Data Offerings on Azure
This module will cover how to identify Azure data services for non-relational workloads. You will also learn about Azure Cosmos DB APIs, Azure Table storage, Azure Blob storage and Azure File storage.
Module 09 - Basic Management Tasks for Non-Relational Data
This module will cover provisioning and deployment of non-relational data services and methods for deployment including ARM templates and Azure Portal. You will also learn how to identify data security components (e.g., firewall, authentication), basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls) and management tools for non-relational data.
Module 10 - Analytics Workloads
In this module you will learn about transactional workloads, the difference between a transactional and an analytics workload and the difference between batch and real time. You will also learn data warehousing workloads and how to determine when a data warehouse solution is needed.
Module 11 - Components of a Modern Data Warehouse
In this module you will learn about Azure data services for modern data warehousing such as Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight and modern data warehousing architecture and workload.
Module 12 - Data Ingestion and Processing on Azure
In this module you will learn common practices for data loading, the components of Azure Data Factory (e.g., pipeline, activities, etc.) and data processing options (e.g., HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Factory).
Module 13 - Data Visualization in Microsoft Power BI
In this module we will cover the role of paginated reporting, the role of interactive reports and the role of dashboards. You will also learn about the workflow in Power BI.