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DP-900 Practice Test 1

DP-900 Practice Test - Skilltestpro

1 / 80

Which type of database is optimized for Online Transaction Processing (OLTP) workloads?

Data warehouse

NoSQL database

Relational database

Data lake

Graph database

2 / 80

Which Power BI component is used to connect to various data sources, transform data, and create a centralized model that can be used for reports and dashboards?

Power BI Desktop

Power BI Service

Power BI Mobile

Power BI Report Server

Power BI Gateway

3 / 80

What is the primary difference between batch processing and streaming data?

Batch processing is for unstructured data, streaming is for structured data.

Batch processing involves processing data in large chunks at scheduled intervals, while streaming processes data continuously as it arrives.

Batch processing is faster than streaming data.

Streaming data is stored in relational databases, batch processing in non-relational databases.

Batch processing requires more compute resources than streaming.

4 / 80

Which role is typically responsible for designing, building, and maintaining the data pipelines that move and transform data from various sources into analytical systems?

Database Administrator

Data Analyst

Data Scientist

Data Engineer

Business User

5 / 80

An organization needs to store product catalog information that has a flexible schema, where different products might have different attributes, and needs fast querying capabilities. Which Azure Cosmos DB API is most suitable for this scenario?

SQL (Core) API

Cassandra API

MongoDB API

Gremlin API

Table API

6 / 80

Which type of non-relational data store is optimized for storing large amounts of unstructured binary data, such as images, videos, documents, and backups?

Azure Blob storage

Azure Table storage

Azure File storage

Azure Cosmos DB

Azure Cache for Redis

7 / 80

Which Azure SQL family offering is a fully managed Platform as a Service (PaaS) database service that is ideal for modern cloud applications requiring high availability and scalability without managing the underlying infrastructure?

SQL Server on Azure Virtual Machines

Azure SQL Managed Instance

Azure SQL Database

Azure Synapse Analytics

Azure Database for PostgreSQL

8 / 80

What is the primary purpose of normalization in a relational database?

To speed up data retrieval.

To reduce data redundancy and improve data integrity.

To allow for more complex queries.

To store unstructured data efficiently.

To encrypt sensitive data.

9 / 80

A company needs to store a large volume of sensor data from IoT devices, which arrives continuously and needs immediate processing. Which type of data workload does this scenario represent?

Transactional workload

Batch processing workload

Analytical workload

Real-time analytics workload

ETL workload

10 / 80

Which type of data is stored in a fixed schema, typically in tables with rows and columns, and is well-suited for relational databases?

Semi-structured data

Binary data

Streamed data

Unstructured data

Structured data

11 / 80

Which term describes data that is organized into a predefined schema, such as rows and columns in a table, before it is stored?

Streaming data

Unstructured data

Metadata

Semi-structured data

Binary large object data

Structured data

12 / 80

Which term describes data that has some organizational properties, such as tags or key-value pairs, but does not conform to a rigid, predefined tabular schema?

Unstructured data

Semi-structured data

Binary large object data

Metadata

Streaming data

Structured data

13 / 80

Which term describes data such as images, videos, and audio files that has no predefined structure or schema?

Unstructured data

Relational data

Metadata

Structured data

Semi-structured data

Streaming data

14 / 80

Which term describes data that is generated continuously and processed incrementally as it arrives, such as sensor readings or social media feeds?

Metadata

Batch data

Master data

Streaming data

Structured data alone

Reference data

15 / 80

Which term describes a large volume of data that is collected over a period and then processed together as a single unit, rather than incrementally?

Streaming data

Reference data

Master data

Batch data

Structured data alone

Metadata

16 / 80

Which term describes data about data, such as a file's creation date, author, or file size, providing context about the actual content?

Structured data

Unstructured data

Transactional data

Semi-structured data

Metadata

Master data

17 / 80

Which core data workload type is optimized for handling a high volume of small, frequent transactions, such as processing individual retail sales?

ETL processing alone

Data archiving alone

Streaming processing alone

Batch processing alone

Online Analytical Processing (OLAP)

Online Transaction Processing (OLTP)

18 / 80

Which core data workload type is optimized for complex queries and aggregations across large volumes of historical data, such as analyzing sales trends over several years?

Streaming processing alone

A basic file storage system alone

Online Transaction Processing (OLTP)

Online Analytical Processing (OLAP)

Batch processing alone, without the specific analytical query optimization focus

A simple key-value lookup alone

19 / 80

Which term describes the process of extracting data from source systems, transforming it into a desired format, and loading it into a destination system such as a data warehouse?

OLAP alone, without the specific extract-transform-load process description

ETL (Extract, Transform, Load)

A simple data encryption operation

A simple file compression operation

A simple backup operation

OLTP

20 / 80

Which variation of the ETL process loads raw data into the destination system first, and then performs the transformation step within that destination system?

ELT (Extract, Load, Transform)

OLAP alone

ETL (Extract, Transform, Load), which transforms the data before loading it into the destination system

OLTP

A simple backup operation

A simple file compression operation

21 / 80

Which data-related role is primarily responsible for designing, implementing, and maintaining database systems, ensuring performance, security, and availability?

A business analyst, who focuses on business requirements rather than administering database systems

A data steward, who focuses on data governance rather than the technical administration of database systems

A data analyst, who focuses on interpreting data rather than administering the underlying database systems

A database administrator (DBA)

A data scientist, who focuses on building predictive models rather than administering database systems

A data engineer, who focuses more on building data pipelines and preparing data for analytics rather than day-to-day database administration

22 / 80

Which data-related role is primarily responsible for building and maintaining the data pipelines and infrastructure that move and transform data for analytics and reporting?

A database administrator, who focuses more on the ongoing operation and maintenance of database systems rather than building broader data pipelines

A data analyst, who focuses on interpreting already-prepared data rather than building the pipelines that prepare it

A data steward

A data engineer

A business analyst

A data scientist, who focuses on building predictive models rather than the underlying data pipeline infrastructure

23 / 80

Which data-related role is primarily responsible for interpreting data and creating reports or visualizations to help business stakeholders make decisions?

A network administrator

A systems architect

A data scientist, who typically focuses more on predictive modeling and advanced statistical techniques than standard business reporting

A data engineer, who focuses on building data pipelines rather than interpreting the resulting data

A database administrator, who focuses on administering database systems rather than interpreting data and creating reports

A data analyst

24 / 80

Which data-related role focuses on building predictive models and applying advanced statistical and machine learning techniques to extract insights from data?

A network administrator

A data engineer, who focuses on data pipeline infrastructure rather than predictive modeling

A data scientist

A data analyst, who focuses more on descriptive reporting and standard business intelligence than advanced predictive modeling

A systems architect

A database administrator, who focuses on database administration rather than predictive modeling

25 / 80

Which term describes the practice of ensuring an organization's data is accurate, consistent, secure, and used appropriately across its lifecycle?

Data engineering, which focuses on building pipelines rather than the broader governance framework

Data replication, which is a specific technical mechanism rather than the broader governance practice

Data mining, which is a specific analytical technique rather than the broader governance practice

Data warehousing, which is a specific storage architecture rather than the broader governance practice

Data streaming, which is a specific data movement pattern rather than the broader governance practice

Data governance

26 / 80

Which of the CIA triad principles most directly relates to ensuring data has not been altered or corrupted in an unauthorized manner?

Integrity

Confidentiality

Non-repudiation

Authentication

Availability

Authorization

27 / 80

Which term describes a formal set of rules governing the naming, format, and definition of common data elements used consistently across an organization?

A data lake, which is a storage repository rather than a formal set of naming and definition rules

A data model, which describes the structure of a specific dataset rather than an organization-wide naming and definition standard

A data dictionary (or data standard)

A data warehouse, which is a specific storage architecture rather than a formal set of naming and definition rules

A data mart, which is a subject-specific subset of a data warehouse rather than a formal set of naming and definition rules

A data pipeline, which is a data movement mechanism rather than a formal set of naming and definition rules

28 / 80

Which term describes core, authoritative data about key business entities, such as customers or products, that is shared and referenced across multiple systems within an organization?

Streaming data, which describes a data movement pattern rather than the authoritative core business entity information

Metadata, which describes data about data rather than the authoritative core business entity information

Transactional data, which records individual business events rather than the authoritative core entity information itself

Archived data, which describes retained historical data rather than the authoritative core business entity information

Log data, which records system events rather than the authoritative core business entity information

Master data

29 / 80

Which term describes data recording the details of a specific business event, such as an individual sales order or a payment transaction?

Transactional data

Streaming data alone, which describes a movement pattern rather than the specific content type

Master data, which describes core, relatively stable business entities rather than individual, discrete events

Metadata

Archived data alone

Reference data alone

30 / 80

Which term describes relatively static, standardized data used to categorize or classify other data, such as a list of valid country codes or currency codes?

Streaming data

Transactional data, which records specific business events rather than a standardized classification list

Reference data

Metadata

Master data, which represents core business entities rather than a standardized classification list

Archived data

31 / 80

Which term describes a column, or set of columns, that uniquely identifies each row in a relational table?

A constraint, which is a broader rule category rather than specifically the unique row identifier

A trigger, which is an automated action rather than a unique row identifier

An index, which improves query performance rather than serving as the row's unique identifier

A foreign key, which references a primary key in another table rather than uniquely identifying rows in its own table

A primary key

A view, which is a saved query rather than a unique row identifier

32 / 80

Which term describes a column in one table that references the primary key of another table, establishing a relationship between the two tables?

An index

A constraint alone, without specifically referencing another table's primary key

A view

A primary key, which uniquely identifies rows in its own table rather than referencing another table's primary key

A foreign key

A trigger

33 / 80

Which set of properties ensures that database transactions are processed reliably, guaranteeing that a transaction either fully completes or has no effect at all?

ACID properties (Atomicity, Consistency, Isolation, Durability)

CAP theorem properties, which describe trade-offs in distributed systems rather than the specific transaction reliability guarantee

BASE properties, which describe a different consistency model typically associated with some NoSQL databases rather than strict relational transaction guarantees

OLAP properties

ETL properties

CRUD properties, which describe basic data operations rather than the specific transaction reliability guarantee

34 / 80

Within the ACID properties, which specific property ensures that a transaction is treated as a single, indivisible unit that either fully succeeds or fully fails?

Consistency, which ensures the database moves from one valid state to another rather than specifically the all-or-nothing execution

Availability, which is not one of the four ACID properties

Atomicity

Isolation, which ensures concurrent transactions do not interfere with each other rather than specifically the all-or-nothing execution

Partition tolerance, which is not one of the four ACID properties

Durability, which ensures committed changes persist rather than specifically the all-or-nothing execution

35 / 80

Within the ACID properties, which specific property ensures that once a transaction has been committed, its changes will persist even in the event of a system failure?

Atomicity, which ensures all-or-nothing execution rather than specifically persistence after commitment

Partition tolerance

Availability

Durability

Consistency, which ensures valid state transitions rather than specifically persistence after commitment

Isolation, which ensures concurrent transactions do not interfere with each other rather than specifically persistence after a system failure

36 / 80

Which database design process organizes tables and relationships to minimize data redundancy and improve data integrity, often involving splitting data into multiple related tables?

Normalization

Denormalization, which is the opposite process, intentionally introducing some redundancy for performance reasons

Sharding, which is focused on distributing data across multiple databases rather than reducing redundancy through table structure

Partitioning, which is focused on splitting data across storage for scalability rather than reducing redundancy through table structure

Replication, which is focused on copying data for availability rather than reducing redundancy through table structure

Indexing, which is focused on query performance rather than reducing redundancy through table structure

37 / 80

Which database design practice intentionally introduces some data redundancy, often by combining tables, to improve read query performance at the cost of increased storage and potential update complexity?

Replication alone

Partitioning alone

Sharding alone

Normalization, which is the opposite process, focused on reducing redundancy rather than intentionally introducing it

Indexing alone, which improves query performance without necessarily restructuring or duplicating table data

Denormalization

38 / 80

Which database object is a database structure that improves the speed of data retrieval operations on a table, at the cost of additional storage and slightly slower write operations?

A trigger, which is an automated action rather than a structure specifically designed to speed up retrieval

A stored procedure, which is a precompiled set of SQL statements rather than a structure specifically designed to speed up retrieval

A constraint, which enforces data rules rather than specifically speeding up retrieval

An index

A schema, which is an organizational namespace rather than a structure specifically designed to speed up retrieval

A view, which is a saved, virtual query result rather than a physical structure specifically designed to speed up retrieval

39 / 80

Which database object represents a saved, virtual table based on the result of a stored SQL query, which can be queried like a regular table without physically duplicating the underlying data?

An index, which speeds up retrieval rather than representing a saved, virtual query result

A constraint, which enforces a data rule rather than representing a saved, virtual query result

A trigger, which is an automated action rather than a saved, virtual query result

A schema, which is an organizational namespace rather than a saved, virtual query result

A view

A stored procedure, which is a callable set of SQL statements rather than a saved, virtual query result table

40 / 80

Which database object is a set of SQL statements stored and precompiled within the database, which can be executed by calling it, often improving performance and reusability?

A stored procedure

A trigger, which executes automatically in response to an event rather than being explicitly called like a stored procedure

A schema, which is an organizational namespace rather than a callable, executable block of logic

A constraint, which enforces a data rule rather than representing a callable, executable block of logic

An index, which speeds up retrieval rather than representing a callable, executable block of logic

A view, which represents a saved query result rather than a callable, executable block of logic

41 / 80

Which Azure relational database service provides a fully managed SQL Server database engine as a Platform as a Service (PaaS) offering, without requiring management of the underlying operating system?

Azure SQL Database

Azure Table Storage, which is a NoSQL key-value store rather than a relational SQL Server-based service

Azure Cosmos DB, which is a NoSQL database rather than a relational SQL Server-based service

SQL Server on Azure Virtual Machines, which is an IaaS offering requiring OS-level management

Azure Database for MySQL, which is based on the MySQL engine rather than SQL Server

Azure Database for PostgreSQL, which is based on the PostgreSQL engine rather than SQL Server

42 / 80

Which Azure relational database offering provides near-complete compatibility with an on-premises SQL Server instance, including support for SQL Server Agent and cross-database queries, while still being a managed PaaS service?

Azure SQL Database, which offers slightly less feature parity with on-premises SQL Server, particularly around certain instance-level features

SQL Server on Azure Virtual Machines, which is an IaaS offering rather than a managed PaaS service

Azure Cosmos DB

Azure Database for PostgreSQL

Azure SQL Managed Instance

Azure Database for MySQL

43 / 80

Which Azure relational database deployment option provides the greatest level of control over the operating system and database engine configuration, at the cost of requiring the customer to manage patching and maintenance themselves?

SQL Server on Azure Virtual Machines (IaaS)

Azure SQL Database, which is a PaaS offering with less OS-level control but far less management overhead

Azure Cosmos DB, which is a NoSQL PaaS offering

Azure SQL Managed Instance, which is a PaaS offering with less OS-level control but far less management overhead

Azure Database for PostgreSQL Flexible Server, which is a PaaS offering

Azure Database for MySQL Flexible Server, which is a PaaS offering

44 / 80

Which Azure service provides a fully managed, open-source relational database compatible with the PostgreSQL engine?

Azure SQL Managed Instance, which is based on the SQL Server engine rather than PostgreSQL

Azure Database for MySQL, which is based on the MySQL engine rather than PostgreSQL

Azure SQL Database, which is based on the SQL Server engine rather than PostgreSQL

Azure Cosmos DB

Azure Synapse Analytics

Azure Database for PostgreSQL

45 / 80

Which Azure service provides a fully managed, open-source relational database compatible with the MySQL engine?

Azure SQL Managed Instance, which is based on the SQL Server engine rather than MySQL

Azure Database for MySQL

Azure Cosmos DB

Azure Synapse Analytics

Azure SQL Database, which is based on the SQL Server engine rather than MySQL

Azure Database for PostgreSQL, which is based on the PostgreSQL engine rather than MySQL

46 / 80

Which Azure SQL Database purchasing model allocates a fixed, dedicated amount of compute and storage resources for a predictable, consistent monthly cost?

The provisioned compute tier

The serverless compute tier, which automatically scales compute based on workload demand and can pause during inactivity, rather than allocating a fixed amount

The Basic service tier alone, which is a specific tier rather than the broader purchasing model description

The Standard service tier alone, which is a specific tier rather than the broader purchasing model description

The Premium service tier alone, which is a specific tier rather than the broader purchasing model description

The hyperscale service tier alone, which is primarily focused on storage scalability rather than describing this specific fixed-allocation billing model

47 / 80

Which Azure SQL Database purchasing model automatically scales compute resources based on workload demand and can automatically pause during periods of inactivity to save cost?

The serverless compute tier

The Standard service tier alone

The Premium service tier alone

The Basic service tier alone

The provisioned compute tier, which allocates a fixed amount of resources rather than automatically scaling and pausing

The hyperscale service tier alone, which is primarily focused on storage scalability rather than this specific automatic-pause billing behavior

48 / 80

Which Azure SQL Database service tier is specifically designed to support very large databases, offering rapid scaling of storage up to very high limits and fast backups regardless of database size?

The provisioned compute tier alone, which describes a billing model rather than this specific storage-scalability service tier

The Standard service tier, which is designed for general-purpose workloads rather than specifically very large databases

The Premium service tier, which offers high performance but is not specifically branded around extreme storage scalability like Hyperscale

The serverless compute tier alone, which describes a billing model rather than this specific storage-scalability service tier

The Basic service tier, which is designed for small, lightweight workloads rather than very large databases

The Hyperscale service tier

49 / 80

Which Azure feature allows a database administrator to create secondary copies of a database in different Azure regions for disaster recovery and read scale-out purposes?

Stored procedures alone, which are reusable SQL logic blocks rather than a cross-region replication capability

Indexing alone, which is focused on query performance within a single database rather than cross-region replication

Views alone, which are saved queries rather than a cross-region replication capability

Normalization alone, which is a design process rather than a cross-region replication capability

Triggers alone, which are automated in-database actions rather than a cross-region replication capability

Geo-replication (active geo-replication or auto-failover groups)

50 / 80

Which factor would most strongly favor choosing Azure SQL Managed Instance over Azure SQL Database for a specific migration project?

The application is built entirely on PostgreSQL rather than SQL Server

The application requires the absolute lowest possible management overhead with no need for instance-level SQL Server feature compatibility

The application has no dependency whatsoever on any SQL Server-specific instance-level features

The existing on-premises SQL Server application relies heavily on instance-level features, such as SQL Server Agent jobs or cross-database queries, that require greater compatibility than Azure SQL Database provides

The organization specifically wants to avoid any compatibility with on-premises SQL Server behavior

The application is built entirely on MySQL rather than SQL Server

51 / 80

Which type of NoSQL database stores data as simple pairs, where each unique key maps to an associated value, well-suited for scenarios like caching or session storage?

A document database, which stores richer, structured documents rather than simple key-value pairs

A time-series database, which is optimized for timestamped data points rather than general simple key-value pairs

A relational database, which uses structured tables with schemas rather than simple key-value pairs

A key-value store

A column-family database, which organizes data into column families rather than simple key-value pairs

A graph database, which models entities and relationships rather than simple key-value pairs

52 / 80

Which type of NoSQL database stores data as flexible, self-describing documents, often in JSON format, allowing each document to have a different structure?

A document database

A key-value store, which stores simpler key-value pairs rather than richer, flexible documents

A relational database, which requires a rigid, predefined schema rather than flexible per-document structure

A time-series database

A graph database

A column-family database

53 / 80

Which type of NoSQL database organizes data into rows and dynamic columns grouped into column families, optimized for very high write throughput and horizontal scalability?

A time-series database

A graph database

A relational database, which uses a fixed, predefined column schema rather than dynamic column families

A column-family database

A key-value store, which is simpler and does not use the specific row/column-family organization

A document database, which stores richer, self-describing documents rather than organizing data into column families

54 / 80

Which type of NoSQL database is specifically optimized for storing and querying entities along with the relationships between them, such as social network connections?

A relational database, which can model relationships via foreign keys but is not as optimized for deep relationship traversal as a dedicated graph database

A time-series database

A graph database

A column-family database

A document database, which can store related data but is not specifically optimized around relationship traversal like a graph database

A key-value store, which is not specifically optimized for modeling complex relationships between entities

55 / 80

Which type of database is specifically optimized for storing and querying data points that are indexed primarily by timestamp, such as sensor readings collected over time?

A time-series database

A column-family database, which is not specifically optimized around timestamp-based indexing and querying, despite some structural similarities

A relational database, which can store timestamped data but is not specifically optimized around this access pattern like a dedicated time-series database

A document database, which is not specifically optimized around timestamp-based indexing and querying

A graph database, which is optimized for relationships rather than specifically timestamp-based data

A key-value store, which is not specifically optimized around timestamp-based indexing and querying

56 / 80

Which Azure service is a globally distributed, multi-model NoSQL database that supports multiple APIs, such as document, key-value, graph, and column-family models, within a single service?

Azure Database for PostgreSQL, which is a relational database service

Azure Blob Storage, which is object storage for unstructured data rather than a multi-model NoSQL database

Azure Cosmos DB

Azure SQL Database, which is a relational database service rather than a multi-model NoSQL service

Azure Table Storage alone, which is specifically a key-value/table storage service rather than supporting multiple distinct NoSQL models

Azure Synapse Analytics, which is an analytics platform rather than a multi-model NoSQL database service

57 / 80

Which Azure Cosmos DB API would be most appropriate for an application already built around MongoDB, allowing it to migrate with minimal code changes?

The Table API, which is designed for key-value/table-style applications rather than MongoDB compatibility

The API for MongoDB (Azure Cosmos DB for MongoDB)

The NoSQL API (Core SQL API), which uses Cosmos DB's native query syntax rather than being specifically MongoDB-wire-protocol compatible

The Cassandra API, which is designed for Cassandra-based applications rather than MongoDB compatibility

The PostgreSQL API, which does not exist as a distinct Cosmos DB API option

The Gremlin API, which is designed for graph-based applications rather than MongoDB compatibility

58 / 80

Which Azure Cosmos DB API would be most appropriate for an application that needs to model and query complex relationships between entities, such as a recommendation engine based on user connections?

The API for MongoDB, which is document-oriented rather than specifically optimized for graph relationship traversal

The Table API, which is key-value oriented rather than specifically optimized for graph relationship traversal

The NoSQL API (Core SQL API), which is document-oriented rather than specifically optimized for graph relationship traversal

The Gremlin API (graph API)

The Cassandra API, which is column-family oriented rather than specifically optimized for graph relationship traversal

The PostgreSQL API, which does not exist as a distinct Cosmos DB API option

59 / 80

Which Azure storage service is a simple, cost-effective NoSQL key-value store, well-suited for storing large amounts of structured, non-relational data such as user profile information?

Azure Files, which provides managed file shares rather than a NoSQL key-value store

Azure Queue Storage, which is designed for message queuing rather than persistent structured key-value data storage

Azure Cosmos DB, which offers a similar Table API but is a more feature-rich, globally distributed, higher-cost multi-model service compared to basic Azure Table Storage

Azure SQL Database, which is a relational database rather than a simple NoSQL key-value store

Azure Blob Storage, which is designed for unstructured object data like files and images rather than structured key-value entities

Azure Table Storage

60 / 80

Which Azure storage service is specifically designed for storing large amounts of unstructured object data, such as images, videos, and backup files, at massive scale?

Azure Blob Storage

Azure SQL Database, which is a relational database rather than an unstructured object storage service

Azure Queue Storage, which is designed for message queuing rather than general-purpose unstructured object storage

Azure Table Storage, which is designed for structured key-value entity data rather than large unstructured object data

Azure Cosmos DB, which is a NoSQL database rather than a general-purpose unstructured object storage service

Azure Files, which provides managed file shares with file-system semantics rather than being the primary object storage service

61 / 80

Which term describes a centralized repository, often using a relational structure, specifically designed to support querying and analysis of large volumes of historical business data?

A transactional database, which is optimized for OLTP workloads rather than large-scale historical analysis

A data lake, which typically stores raw data in its native format rather than a structured, query-optimized analytical repository

A data mart alone, which is a subject-specific subset rather than the overall centralized repository

A content delivery network, which is designed for content distribution rather than analytical data storage

A data warehouse

A message queue, which is designed for asynchronous communication rather than analytical storage

62 / 80

Which term describes a storage repository that can hold vast amounts of raw data in its native format, structured, semi-structured, or unstructured, until it is needed for processing or analysis?

A data lake

A data warehouse, which typically stores curated, structured data optimized for specific analytical queries rather than raw data in its native format

A data mart, which is a subject-specific subset of a data warehouse rather than a repository for raw, native-format data

A message queue

A content delivery network

A relational database, which requires a predefined schema rather than storing raw, native-format data of any type

63 / 80

Which term describes a smaller, subject-specific subset of a data warehouse, tailored to the needs of a particular business unit or team, such as a finance-specific data mart?

A content delivery network

A data lake, which is a broader repository for raw data rather than a curated, subject-specific analytical subset

A data mart

A relational database alone, which is a general storage technology rather than specifically a subject-specific analytical subset

A message queue

A data warehouse, which is the broader, organization-wide repository that a data mart is typically derived from

64 / 80

Which dimensional modeling schema organizes data into a central fact table directly connected to multiple denormalized dimension tables, resembling a star shape?

A snowflake schema, which further normalizes the dimension tables into additional related tables rather than keeping them denormalized

A galaxy schema (fact constellation), which involves multiple fact tables rather than describing this specific single-fact-table star pattern

A third normal form schema, which is a general relational normalization level rather than a specific dimensional modeling pattern

An entity-relationship schema alone, which is a general modeling technique rather than this specific dimensional star pattern

A star schema

A flat file schema, which has no relational structure at all

65 / 80

Which dimensional modeling schema further normalizes the dimension tables of a star schema into additional related tables, reducing redundancy at the cost of more complex queries?

An entity-relationship schema alone

A snowflake schema

A first normal form schema alone, which is a general relational normalization level rather than this specific dimensional modeling pattern

A galaxy schema (fact constellation), which involves multiple fact tables rather than describing this specific dimension-normalization pattern

A flat file schema

A star schema, which keeps dimension tables denormalized rather than further splitting them into additional related tables

66 / 80

Which term describes a central table in a dimensional model that contains measurable, quantitative data, such as sales amounts, along with foreign keys referencing related dimension tables?

A dimension table, which contains descriptive, contextual attributes rather than the central measurable quantitative values

An audit table, which tracks changes rather than serving as the central table of measurable business facts

A lookup table alone, which is a general reference concept rather than specifically this central fact table role

A fact table

A bridge table alone, which resolves many-to-many relationships rather than serving as the central table of measurable facts

A staging table, which is a temporary holding area during ETL processing rather than the central table of measurable business facts

67 / 80

Which term describes a table in a dimensional model that contains descriptive, contextual attributes, such as customer name or product category, used to filter and group data in a fact table?

A dimension table

A lookup table alone, which is a general concept rather than specifically this dimensional-modeling role

An audit table

A staging table, which is a temporary ETL holding area rather than this specific descriptive-attribute role

A fact table, which contains measurable quantitative values rather than the descriptive, contextual attributes

A bridge table alone

68 / 80

Which Azure service is specifically designed as an integrated analytics platform, combining big data and data warehousing capabilities, along with data integration, in a single unified workspace?

Azure Data Factory, which is focused specifically on data integration and orchestration rather than the broader unified analytics and data warehousing platform

Power BI, which is a visualization and reporting tool rather than the broader unified data warehousing and big data analytics platform

Azure Data Lake Storage alone, which is a storage service rather than the broader unified analytics platform

Azure SQL Database, which is a general-purpose relational database rather than a unified big-data-and-warehousing analytics platform

Azure Databricks, which is an Apache Spark-based analytics platform, though not the same integrated Microsoft-native offering as Synapse

Azure Synapse Analytics

69 / 80

Which Azure service is specifically designed to orchestrate and automate data movement and transformation workflows, such as building an ETL or ELT pipeline?

Power BI, which is a visualization tool rather than an orchestration service

Azure Databricks, which is primarily focused on big data processing and analytics using Spark rather than being the primary dedicated orchestration service

Azure Data Factory

Azure Synapse Analytics, which includes similar integration capabilities but is primarily framed as the broader unified analytics platform rather than a standalone orchestration-focused service

Azure Data Lake Storage, which is a storage service rather than an orchestration service

Azure SQL Database, which is a data storage service rather than a data movement and transformation orchestration service

70 / 80

Which Azure Data Factory component represents a single, executable unit of work within a broader data movement or transformation workflow, such as copying data from one location to another?

An activity

A dataset, which represents a specific data structure or reference rather than an executable unit of work

A pipeline, which is the broader logical grouping of multiple activities rather than a single unit of work itself

An integration runtime, which provides the compute infrastructure rather than being the executable unit of work itself

A linked service, which defines a connection to a data source or compute resource rather than an executable unit of work

A trigger, which initiates a pipeline's execution based on a schedule or event rather than being the executable unit of work itself

71 / 80

Which Azure service provides an Apache Spark-based analytics platform, well-suited for large-scale data engineering and data science workloads involving big data processing?

Azure Data Factory, which is focused on orchestration and data movement rather than being the primary Spark-based big data compute engine

Azure Databricks

Azure Content Delivery Network, which is unrelated to big data processing

Azure Table Storage, which is a simple key-value store rather than a big data processing platform

Azure SQL Database, which is a relational database service rather than a Spark-based big data processing platform

Power BI, which is a visualization tool rather than a big data processing platform

72 / 80

Which term describes a data processing approach where data is processed in large chunks at scheduled intervals, rather than continuously as it arrives?

Data replication, which is a data copying mechanism rather than a processing pattern

Transactional processing alone, which describes OLTP workloads rather than this specific scheduled-chunk analytical processing pattern

Master data management, which is a data governance discipline rather than a processing pattern

Batch processing

Stream processing, which processes data continuously and incrementally as it arrives, rather than in scheduled chunks

Real-time processing alone, which is closely associated with stream processing rather than scheduled chunk-based processing

73 / 80

Which term describes a data processing approach where data is processed continuously and incrementally as it arrives, often with very low latency, such as monitoring live sensor data?

OLTP alone, which describes transactional database workloads rather than this specific analytical streaming pattern

Batch processing, which processes data in scheduled chunks rather than continuously as it arrives

Normalization, which is a database design process rather than a data processing pattern

Data replication, which is a copying mechanism rather than a processing pattern

Stream processing

Master data management, which is a governance discipline rather than a processing pattern

74 / 80

Which Azure service is specifically designed for real-time analytics on fast-moving streaming data, such as data ingested from IoT devices or clickstream events?

Azure SQL Database, which is a relational database rather than a dedicated streaming analytics engine

Azure Stream Analytics

Power BI, which is a visualization tool that can consume streaming analytics output but is not itself the streaming processing engine

Azure Content Delivery Network

Azure Table Storage, which is a storage service rather than a streaming analytics processing engine

Azure Data Factory, which is focused on orchestrating batch and pipeline-based data movement rather than being the dedicated real-time streaming analytics engine

75 / 80

Which Azure service acts as a highly scalable event ingestion service, capable of receiving and processing millions of events per second from sources such as applications and IoT devices?

Azure Data Factory, which orchestrates data movement rather than serving as the primary high-throughput event ingestion service

Azure Stream Analytics, which processes streaming data but typically relies on a service like Event Hubs to first ingest the raw event stream

Power BI, which is a visualization tool rather than an event ingestion service

Azure Table Storage, which is a storage service rather than a high-throughput event ingestion service

Azure Event Hubs

Azure SQL Database, which is a relational database rather than an event ingestion service

76 / 80

Which Azure service is a business intelligence and data visualization tool used to create interactive reports and dashboards from various data sources?

Azure Synapse Analytics, which is a broader analytics platform that can integrate with visualization tools like Power BI, rather than being the dedicated visualization and reporting tool itself

Power BI

Azure Databricks, which is a big data processing platform rather than a dedicated business intelligence visualization tool

Azure SQL Database, which is a data storage service rather than a visualization tool

Azure Data Factory, which is a data orchestration tool rather than a business intelligence visualization tool

Azure Event Hubs, which is an event ingestion service rather than a visualization tool

77 / 80

Which Power BI component allows a business user to publish and share interactive reports and dashboards with colleagues within their organization?

A gateway alone, which enables on-premises data connectivity rather than serving as the primary report-sharing platform

A dataset alone, which is the underlying data source rather than the sharing and collaboration platform itself

The Power BI service (Power BI online)

Power BI Desktop alone, which is primarily used for authoring reports locally, prior to publishing them for broader sharing

Power BI Mobile alone, which is primarily used for viewing already-published reports on a mobile device rather than the primary publishing and sharing platform

A dataflow alone, which is a reusable data preparation process rather than the primary report-sharing platform

78 / 80

Which Power BI component is used to author and design reports locally on a desktop computer, connecting to various data sources and building visualizations before publishing?

Power BI Mobile, which is for viewing reports on a mobile device rather than the primary local authoring tool

A dataflow alone

The Power BI service, which is primarily for publishing, sharing, and consuming already-authored reports rather than the primary local authoring tool

A gateway alone

Power BI Desktop

A dataset alone

79 / 80

Which Power BI feature allows on-premises data sources, such as an on-premises SQL Server database, to be securely accessed and refreshed by cloud-based Power BI reports?

Power BI Mobile alone

The Power BI service alone, without the specific gateway component enabling on-premises connectivity

An on-premises data gateway

A dataset alone, without the specific gateway mechanism

Power BI Desktop alone, which is a local authoring tool rather than the specific mechanism enabling secure cloud-to-on-premises connectivity

A dataflow alone, without the specific gateway mechanism

80 / 80

Which combination of Azure services would be most appropriate for building an end-to-end analytics solution that ingests real-time IoT sensor data, processes it with low latency, stores results in a data warehouse, and visualizes trends for business stakeholders?

Azure Data Lake Storage alone, without any dedicated ingestion, real-time processing, warehousing, or visualization components

Azure Table Storage alone, without any dedicated ingestion, real-time processing, warehousing, or visualization components

Azure Content Delivery Network alone, which is unrelated to this analytics workflow

Power BI alone, without any dedicated ingestion, real-time processing, or data warehousing components

Azure Event Hubs (ingestion), Azure Stream Analytics (real-time processing), Azure Synapse Analytics (data warehousing), and Power BI (visualization)

Azure SQL Database alone, without any dedicated ingestion, real-time processing, or visualization components

Your score is

The average score is 69%