This exam will be updated on October 22, 2020. Following the current exam guide, we have included a version of the exam guide with Track Changes set to “On,” showing the changes that will be made to the exam on that date.
Audience Profile
Candidates for this exam should have the foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.
This exam is intended for candidates beginning to work with data in the cloud.
Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.
Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it is not a prerequisite for any of them.
Skills Measured
NOTE: The bullets that appear below each of the skills measured are intended to illustrate how we are assessing that skill. This list is not definitive or exhaustive.
NOTE: In most cases, exams do NOT cover preview features, and some features will only be added to an exam when they are GA (General Availability).
Describe core data concepts (15-20%)
Describe types of core data workloads
- describe batch data
- describe streaming data
- describe the difference between batch and streaming data
- describe the characteristics of relational data
Describe data analytics core concepts
- describe data visualization (e.g., visualization, reporting, business intelligence (BI))
- describe basic chart types such as bar charts and pie charts
- https://chartio.com/learn/charts/how-to-choose-pie-chart-vs-bar-chart/
- describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive)
- Describe ELT and ETL processing describe the concepts of data processing
Describe how to work with relational data on Azure (25-30%)
Describe relational data workloads
- identify the right data offering for a relational workload
- describe relational data structures (e.g., tables, index, views)
Describe relational Azure data services
- describe and compare PaaS, IaaS, and SaaS delivery models
- https://docs.microsoft.com/en-us/azure/security/fundamentals/shared-responsibility
- https://docs.microsoft.com/en-us/learn/modules/cmu-cloud-computing-overview/7-use-cases
- describe Azure SQL Database
- describe Azure Synapse Analytics
- describe SQL Server on Azure Virtual Machine
- describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL
- describe Azure SQL Managed Instance
Identify basic management tasks for relational data
- describe provisioning and deployment of relational data services
- describe the method for deployment including ARM templates and Azure Portal
- https://docs.microsoft.com/en-us/azure/azure-sql/database/arm-templates-content-guide?tabs=single-database
- identify data security components (e.g., firewall, authentication)
- https://docs.microsoft.com/en-us/learn/modules/explore-provision-deploy-relational-database-offerings-azure/5-configure-relational-data-services
- identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from the Internet, authentication, firewalls)
- identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.)
Describe query techniques for data using SQL language
- compare DDL versus DML
- query relational data in PostgreSQL, MySQL, and Azure SQL Database
Describe how to work with non-relational data on Azure (25-30%)
Describe non-relational data workloads
- describe the characteristics of non-relational data
- describe the types of non-relational and NoSQL data
- recommend the correct data store
- determine when to use non-relational data
Describe non-relational data offerings on Azure
- identify Azure data services for non-relational workloads
- describe Azure Cosmos DB APIs
- describe Azure Table storage
- describe Azure Blob storage
- describe Azure File storage
Identify basic management tasks for non-relational data
- describe provisioning and deployment of non-relational data services
- describe method for deployment including ARM templates and Azure Portal
- identify data security components (e.g., firewall, authentication)
- identify basic connectivity issues (e.g., accessing from on-premises, access with Azure
VNets, access from Internet, authentication, firewalls)
- https://docs.microsoft.com/en-us/learn/modules/secure-your-azure-sql-database/
- https://docs.microsoft.com/en-us/azure/azure-sql/database/firewall-configure
- identify management tools for non-relational data
Describe an analytics workload on Azure (25-30%)
Describe analytics workloads
- describe transactional workloads
- describe the difference between a transactional and an analytics workload
- describe the difference between batch and real time
- describe data warehousing workloads
- determine when a data warehouse solution is needed
Describe the components of a modern data warehouse
- describe Azure data services for modern data warehousing such as Azure Data Lake,
Azure Synapse Analytics, Azure Databricks, and Azure HDInsight
- https://docs.microsoft.com/en-us/learn/modules/survey-the-azure-data-platform/
- describe modern data warehousing architecture and workload
Describe data ingestion and processing on Azure
- describe common practices for data loading
- describe the components of Azure Data Factory (e.g., pipeline, activities, etc.)
- describe data processing options (e.g., HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)
Describe data visualization in Microsoft Power BI
- describe the role of paginated reporting
- describe the role of interactive reports describe the role of dashboards
- describe the workflow in Power BI
The exam guide below shows the changes that will be implemented on October 22, 2020.
Audience Profile
Candidates for this exam should have the foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services.
This exam is intended for candidates beginning to work with data in the cloud.
Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical.
Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but it is not a prerequisite for any of them.
Skills Measured
NOTE: The bullets that appear below each of the skills measured are intended to illustrate how we are assessing that skill. This list is not definitive or exhaustive.
NOTE: In most cases, exams do NOT cover preview features, and some features will only be added to an exam when they are GA (General Availability).
Describe core data concepts (15-20%)
Describe types of core data workloads
- describe batch data
- describe streaming data
- describe the difference between batch and streaming data
- describe the characteristics of relational data
Describe data analytics core concepts
- describe data visualization (e.g., visualization, reporting, business intelligence (BI))
- describe basic chart types such as bar charts and pie charts
- describe analytics techniques (e.g., descriptive, diagnostic, predictive, prescriptive, cognitive)
- describe ELT and ETL processing
describe the concepts of data processing
Describe how to work with relational data on Azure (25-30%)
Describe relational data workloads
- identify the right data offering for a relational workload
- describe relational data structures (e.g., tables, index, views)
Describe relational Azure data services
- describe and compare PaaS, IaaS, and SaaS solutions
delivery models - describe Azure SQL database services including Azure SQL Database, Azure SQL
Managed Instance, and SQL Server on Azure Virtual Machine Database
- describe Azure Synapse Analytics
describe SQL Server on Azure Virtual Machine- describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQL
describe Azure SQL Managed Instance
Identify basic management tasks for relational data
- describe provisioning and deployment of relational data services
- describe method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)
ARM templatesand Azure Portal - identify data security components (e.g., firewall, authentication)
- identify basic connectivity issues (e.g., accessing from on-premises, access with Azure VNets, access from Internet, authentication, firewalls)
- identify query tools (e.g., Azure Data Studio, SQL Server Management Studio, sqlcmd utility, etc.)
Describe query techniques for data using SQL language
- compare Data Definition Language (DDL) versus Data Manipulation Language (DML)
- query relational data in
- azure SQL D
Batabase, Azure Database for PostgreSQL, and Azure Database for MySQL PostgreSQL, MySQL, and Azure SQL Database
Describe how to work with non-relational data on Azure (25-30%)
Describe non-relational data workloads
describe the characteristics of non-relational data describe the types of non-relational and NoSQL data
- recommend the correct data store
- determine when to use non-relational data
Describe non-relational data offerings on Azure
- identify Azure data services for non-relational workloads
- describe Azure Cosmos DB APIs
- describe Azure Table storage
- describe Azure Blob storage
- describe Azure File storage
Identify basic management tasks for non-relational data
- describe provisioning and deployment of non-relational data services
- describe the method for deployment including the Azure portal, Azure Resource Manager templates, Azure PowerShell, and the Azure command-line interface (CLI)
ARM templatesand Azure Portal - identify data security components (e.g., firewall, authentication)
- identify basic connectivity issues (e.g., accessing from on-premises, access with Azure
VNets, access from the Internet, authentication, firewalls)
- identify management tools for non-relational data
Describe an analytics workload on Azure (25-30%)
Describe analytics workloads
- describe transactional workloads
- describe the difference between a transactional and an analytics workload
- describe the difference between batch and real-time
- describe data warehousing workloads
- determine when a data warehouse solution is needed
Describe the components of a modern data warehouse
- describe Azure data services for modern data warehousing such as Azure Data Lake,
Azure Synapse Analytics, Azure Databricks, and Azure HDInsights
- describe modern data warehousing architecture and workload
Describe data ingestion and processing on Azure
- describe common practices for data loading
describe the components of Azure Data Factory (e.g., pipeline, activities, etc.)
- describe data processing options (e.g., Azure HDInsight
HDI, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)
Describe data visualization in Microsoft Power BI
- describe the role of paginated reporting
- describe the role of interactive reports
- describe the role of dashboards
- describe the workflow in Power BI