The content of this exam will be updated on October
25, 2021. Please download the skills measured document below to see what will be
changing.
NOTE: Passing score: 700. Learn more about exam scores here.
Languages: English, Japanese, Chinese (Simplified), Korean, French, German,
Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi
Arabia), Chinese (Traditional), Italian
Retirement date: none
Prove that you can describe the following: core data concepts; how to work with
relational data on Azure; how to work with non-relational data on Azure; and an
analytics workload on Azure.
Skills measured
The content of this exam will be updated on October 25, 2021. Please
download the exam skills outline below to see what will be changing.
Describe core data concepts (15-20%)
Describe how to work with relational data on Azure (25-30%)
Describe how to work with non-relational data on Azure (25-30%)
Describe an analytics workload on Azure (25-30%)
This exam will be updated on October 25, 2021.
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 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: Most questions cover features that are General Availability (GA). The exam
may contain questions on Preview features if those features are commonly used.
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
describe Azure SQL family of products including Azure SQL Database, Azure SQL
Managed Instance, and SQL Server on Azure Virtual Machines
describe Azure Synapse Analytics
describe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure
Database for MySQL
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)
identify data security components (e.g., firewall, authentication)
identify basic connectivity issues (e.g., accessing from on-premises, access
with from
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 Database, Azure Database for PostgreSQL,
and Azure
Database for MySQL
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 the Azure portal, Azure Resource
Manager
templates, Azure PowerShell, and the Azure command-line interface (CLI)
identify data security components (e.g., firewall, authentication, encryption)
identify basic connectivity issues (e.g., accessing from on-premises, access
with from
Azure VNets, access from 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 Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure
HDInsight
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, 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
QUESTION 1
Which statement is an example of Data Manipulation Language (DML)?
A. REVOKE
B. DISABLE
C. INSERT
D. GRANT
Correct Answer: C
QUESTION 2
You have a SQL query that combines customer data and order data. The query
includes calculated columns.
You need to create a database object that would allow other users to rerun the
same SQL query.
What should you create?
A. an index
B. a view
C. a scalar function
D. a table
Correct Answer: B
QUESTION 3
You have an Azure Cosmos DB account that uses the Core (SQL) API.
Which two settings can you configure at the container level? Each correct answer
presents a complete solution. (Choose two.)
NOTE: Each correct selection is worth one point.
A. the throughput
B. the read region
C. the partition key
D. the API
Correct Answer: AC
QUESTION 4
You need to store data by using Azure Table storage.
What should you create first?
A. an Azure Cosmos DB instance
B. a storage account
C. a blob container
D. a table
Correct Answer: B
QUESTION 5
What should you use to build a Microsoft Power BI paginated report?
A. Charticulator
B. Power BI Desktop
C. the Power BI service
D. Power BI Report Builder
Correct Answer: D
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