Explore data roles and services

Which role is responsible for the design, implementation, maintenance, and operational aspects of on-premises and cloud-based database systems — including overall availability, consistent performance, backup and recovery plans, and managing data security? a) Database administrator b) Data engineer c) Data analyst d) AI engineer

a

Which role manages infrastructure and processes for data integration across the organization, applying data cleaning routines, identifying data governance rules, and implementing pipelines to transfer and transform data between systems? a) Database administrator b) Data engineer c) Data analyst d) AI engineer

b

Which role explores and analyzes data to create visualizations and charts that enable organizations to make informed decisions, and designs and builds analytical models? a) Database administrator b) Data engineer c) Data analyst d) AI engineer

c

Which role builds and integrates AI-powered features and workflows, working with large language models, machine learning pipelines, and data sources to enable intelligent scenarios? a) Database administrator b) Data engineer c) Data analyst d) AI engineer

d

The cloud delivery model in which Microsoft manages the underlying infrastructure — servers, patching, backups — so you focus on your data and applications. a) PaaS (platform-as-a-service) b) SaaS (software-as-a-service) c) IaaS (infrastructure-as-a-service) d) DBaaS (database-as-a-service)

a

The cloud delivery model in which the entire product is delivered as a ready-to-use service over the internet, with no installation or infrastructure management required. a) PaaS b) SaaS c) IaaS d) On-premises

b

Complete the sentence: "Azure ____ is the collective name for a family of relational database solutions based on the Microsoft SQL Server database engine." a) Synapse b) Cosmos c) SQL d) Storage

c

Which Azure SQL service is a fully managed platform-as-a-service (PaaS) database hosted in Azure? a) Azure SQL Managed Instance b) Azure SQL VM c) Azure Database for PostgreSQL d) Azure SQL Database

d

Which Azure SQL service is a hosted instance of SQL Server with automated maintenance, allowing more flexible configuration than Azure SQL Database but with more administrative responsibility for the owner? a) Azure SQL Managed Instance b) Azure SQL Database c) Azure SQL VM d) Azure Database for MySQL

a

Which Azure SQL service provides a virtual machine with an installation of SQL Server, allowing maximum configurability with full management responsibility? a) Azure SQL Database b) Azure SQL VM c) Azure SQL Managed Instance d) Azure Cosmos DB

b

Complete the sentence: "Azure Database for ____ is a simple-to-use open-source database management system commonly used in LAMP stack apps." a) PostgreSQL b) MariaDB c) MySQL d) SQLite

c

Which Azure service is a hybrid relational-object database where you can store data in relational tables but also store custom data types with their own nonrelational properties? a) Azure Database for MySQL b) Azure SQL Database c) Azure Cosmos DB d) Azure Database for PostgreSQL

d

Which Azure service is a global-scale nonrelational (NoSQL) database system that supports multiple APIs, enabling you to store and manage data as JSON documents, key-value pairs, column-families, and graphs? a) Azure Cosmos DB b) Azure SQL Managed Instance c) Azure Database for PostgreSQL d) Azure Data Explorer

a

In Azure Storage, which capability provides scalable, cost-effective storage for binary files? a) File shares b) Blob containers c) Tables d) Queues

b

In Azure Storage, which capability provides network file shares such as you typically find in corporate networks? a) Blob containers b) Tables c) File shares d) Data lakes

c

In Azure Storage, which capability provides key-value storage for applications that need to read and write data values quickly? a) Blob containers b) File shares c) Queues d) Tables

d

In terms of Azure Storage, what is a data lake? a) Blob storage with a hierarchical namespace that enables files to be organized in folders in a distributed file system b) A fully relational SQL engine optimized for read operations c) A key-value store used by applications for fast reads and writes d) A preaggregated analytical model across dimensions

a

Which Azure service enables you to define and schedule data pipelines to transfer and transform data, and is used by data engineers to build ETL solutions that populate analytical data stores? a) Azure Stream Analytics b) Azure Data Factory c) Azure Data Explorer d) Microsoft Fabric

b

Which platform is Microsoft's unified software-as-a-service (SaaS) analytics platform that brings data engineering, data warehousing, real-time analytics, data science, and Power BI together in a single browser-based workspace? a) Azure Databricks b) Azure Data Factory c) Microsoft Fabric d) Microsoft Purview

c

What is the name of the shared storage layer that Microsoft Fabric works on top of? a) Delta Lake b) Azure Data Lake Storage c) Blob containers d) OneLake

d

Within Microsoft Fabric, which integrated capability provides data warehouse analytics? a) Fabric Warehouse b) Fabric Lakehouse c) Fabric Data Factory d) Real-Time Intelligence

a

Within Microsoft Fabric, which integrated capability is used for data visualization? a) Fabric Lakehouse b) Power BI c) Fabric Warehouse d) Fabric Data Factory

b

Which Fabric workload provides context on business entities and data, building on OneLake and Power BI semantic models so that people, tools, and AI agents share the same definitions for concepts like Customer, Order, or Product? a) Fabric Lakehouse b) Fabric Data Factory c) Fabric IQ d) Real-Time Intelligence

c

Which Microsoft platform do data analysts use to connect to data sources, build interactive reports and dashboards, and share insights across their organization? a) Microsoft Purview b) Microsoft Foundry c) Azure Data Factory d) Power BI

d

In Microsoft Fabric, Power BI connects to data through which structured analytical layers that define measures, relationships, and business logic? a) Semantic models b) Data lakes c) Blob containers d) Column families

a

Which cloud analytics platform is built on Apache Spark and optimized for large-scale data engineering, data science, and SQL analytics over open lakehouse formats — primarily Delta Lake? a) Microsoft Fabric b) Azure Databricks c) Azure Data Explorer d) Azure Stream Analytics

b

Which Azure service is a real-time stream processing engine that captures a stream of data from an input, applies a query to extract and manipulate data from that stream, and writes the results to an output? a) Azure Data Factory b) Azure Data Explorer c) Azure Stream Analytics d) Azure Databricks

c

Which Azure service is a fully managed, standalone big data analytics platform that offers high-performance querying of log and telemetry data? a) Azure Stream Analytics b) Azure Data Factory c) Microsoft Fabric d) Azure Data Explorer

d

Which Microsoft service provides enterprise-wide data governance and discoverability, letting you create a map of your data and track data lineage across multiple data sources and systems? a) Microsoft Purview b) Microsoft Foundry c) Microsoft Fabric d) Power BI

a

Which Microsoft platform is a unified Azure platform-as-a-service (PaaS) for enterprise AI operations, model builders, and application development, providing the tools, model access, and infrastructure AI engineers use to design, test, and deploy intelligent solutions? a) Microsoft Fabric b) Microsoft Foundry c) Microsoft Purview d) Azure Machine Learning Studio

b

Which role typically provisions and manages Azure SQL database systems to support line of business (LOB) applications that need to store transactional data? a) Data analyst b) AI engineer c) Database administrator d) Software developer

c

Which role owns the management and monitoring of data pipelines to ensure that data loads perform as expected? a) Database administrator b) Data analyst c) AI engineer d) Data engineer

d

Which role processes raw data into relevant insights based on identified business requirements? a) Data analyst b) Data engineer c) Database administrator d) AI engineer

a

Which role works with large language models to enable intelligent scenarios such as chat-over-your-data, content generation, and automated classification? a) Data analyst b) AI engineer c) Data engineer d) Database administrator

b

Which role is responsible for ensuring that the privacy of data is maintained within the cloud and spanning from on-premises to the cloud data stores? a) Database administrator b) Data analyst c) Data engineer d) AI engineer

c

Which role grants privileges over data and grants or denies access to users as appropriate? a) Data engineer b) Data analyst c) AI engineer d) Database administrator

d

Microsoft Copilot in Azure can help database administrators and developers generate which query language using natural language? a) T-SQL b) DAX c) PySpark d) KQL

a

In many organizations, who often provisions and manages Azure Cosmos DB data storage as part of the overall application architecture rather than a database administrator? a) Data analysts b) Software developers c) Business users d) Data scientists

b

The Azure Cosmos DB extension for Visual Studio Code includes which AI-assisted feature (in preview) that developers can use to generate and explain queries using natural language? a) Copilot for Cosmos b) Query Explainer c) Query advisor d) Genie Code

c

Within Microsoft Fabric, which integrated capability covers a SQL database and Cosmos DB? a) Fabric Lakehouse b) Fabric Data Factory c) Real-Time Intelligence d) Databases

d

Power BI includes built-in AI features that data analysts can use to: a) Summarize reports, suggest visualizations, generate DAX measures, and create written narratives from data using natural language b) Provision virtual machines running SQL Server c) Enforce data lineage across enterprise sources d) Capture and query real-time streaming data

a

Microsoft Fabric includes Copilot features that data professionals can use to: a) Replace the need for data governance entirely b) Build pipelines, write SQL, generate notebook code, and explore data using natural language c) Automatically convert NoSQL databases into relational ones d) Provision physical servers for the workspace

b

Azure Databricks includes built-in AI features that data engineers and analysts can use to: a) Generate T-SQL scripts for Azure SQL Database b) Create data lineage maps across sources c) Write Spark code, generate SQL queries, and explain complex notebook logic using natural language d) Build Power BI dashboards automatically

c

The following are key data-related roles described in this module as common in most medium to large organizations, EXCEPT: a) Database administrator b) Data engineer c) Data analyst d) Data scientist

d

In some organizations, the same person might provision a transactional database in their role as database administrator, and then create a pipeline to transfer data to a data warehouse in their role as data engineer. What does this illustrate? a) That roles define differentiated tasks and responsibilities, but the same person may perform multiple roles b) That database administrators are also required to be data engineers by definition c) That all data roles share identical responsibilities d) That data warehouses can only be populated by database administrators

a

Data analysts may query Azure SQL databases directly to create reports, but in large organizations the data is generally combined with data from other sources in what, to support enterprise analytics? a) A blob container b) An analytical data store c) A key-value table d) A column family

b

Data engineers may use Azure SQL database systems as sources for data pipelines that perform which operations to ingest the transactional data into an analytical system? a) CRUD b) OLAP c) ETL d) ACID

c

Why don't Fabric users manage servers or clusters themselves? a) Because Fabric is a relational database engine b) Because Fabric runs only on-premises c) Because Fabric requires Databricks to run the infrastructure d) Because Fabric is a SaaS platform — you create workspaces and items, and Microsoft runs the infrastructure

d

Azure Data Factory pipelines can be integrated with other Azure services, enabling you to: a) Ingest data from cloud data stores, process the data using cloud-based compute, and persist the results in another data store b) Replace Power BI for creating dashboards c) Run machine learning training jobs without any data d) Store binary files as BLOBs only

a

Fabric Data Factory pipelines work directly with: a) Azure SQL VM only b) OneLake and other Fabric items c) Cosmos DB graphs exclusively d) Power BI reports only

b

Microsoft Fabric requires data professionals to manage the underlying servers and clusters themselves.

False

Power BI is available only as part of Microsoft Fabric.

False

Microsoft Purview is a real-time stream processing engine for capturing and querying streaming data.

False

Because AI assistance is central to the AI engineer's work, design decisions, evaluation, and responsible deployment of AI systems are delegated to AI tools.

False

The Fabric IQ workload and its ontology item are currently in preview.

True

A data engineer may work with a wide range of data platform technologies, including relational and nonrelational databases, file stores, and data streams.

True

Azure Cosmos DB instances are always provisioned and managed by a database administrator.

False

Azure Databricks is a managed service in Azure and a common choice for teams that need code-first Spark and notebook-based workflows.

True

Microsoft Foundry is a database service for storing JSON documents.

False

Application developers and software engineers are not considered technical professionals who work with data.

False