These Data Virtualization multiple-choice questions and their answers will help you strengthen your grip on the subject of Data Virtualization. You can prepare for an upcoming exam or job interview with these 70+ Data Virtualization MCQs.
So scroll down and start answering.
A. Heterogeneity
B. Autonomy
C. Schema Mapping
Analyze the information given below and answer the question that follows.
"Data integration includes the practices, architectural techniques, and tools used to gain consistent access to data. regardless of data structure type or group, in order to meet the requirements of applications and business processes."
What is the source of the given information?
A.
Gartner
B.
Forrester
C.
Wayne Eckerson
D.
In which of the following layers of data abstraction architecture, data sources are integrated into the abstraction?
A.
Application layer
B. Physical Layer
C. Business Layer
D.
Value-added tasks such as name aliasing, value formatting and data type casting are performed in which of the following layers?
A. Application Layer
B. Business Layer
C. Physical Layer
D.
Which of the following components Of the logical data warehouse provides abstracted and semantic layer overview of enterprise data across virtualized, distributed and repository-based sources?
A.
Data Virtualization
B. Distributed Process
C.
Repository Management
D.
Taxonomy/Ontology Resolution
A. Application layer
B. Data consumer layer
C. Business layer
D. Physical layer
A. Typically. data is dynamic but dated.
B. Typically, no data drilldown capabilities are available.
C. Difficult to accommodate changes in data source schema.
D. Cannot actively monitor data changes
Generally six approaches are used for data integration problem: manual integration, common user interface, integration by applications, integration by middleware, uniform data access and common data storage. Which of the following systems use all the six integration approaches simultaneously?
A. Workflow Management System
B. Personal Data integration system
C. Medicated Query System
D. Dataspace system
A. Yes
B. No
Which of the following is an example of the common data storage approach toward data integration problem?
A.
Mediated query systems
B.
Operational data stores
C.
Federated database systems
Which Of the following can be used in order to access virtualized data?
1. Enterprise service bus
2. Object-relational mapper
3. Dedicated data virtualization server
A.
Only 3 can be used
B. Only 1 and 3 can be used
C. Only 2 and 3 can be used
D. All 1, 2 and 3 can be used
E.
A. Yes
B. No
A. Data staging area
B. Data warehouse
C. Data mart
D. None of the above
Analyze the information given below and answer the question that follows.
"The most successful implementation of data virtualization uses a layered architecture that combines
physical and virtual data stores at the appropriate levels to fit different performance requirements for
different areas within the company."
What is the source of the given information?
A.
Gartner
B. Forrester
C. Wayne Eckerson
D.
A. SLA Management
B. Distributed Processes
C. Metadata Management
D. Data Virtualization
Which of the following statements is/are correct about the distributed processes component of logical data warehouse?
1. It is used to integrate big data sources such as Hadoop with distributed processes performed in the cloud.
2. It provides abstracted and semantic layer overview of enterprise data across virtualized sources.
3. It provides data governance, auditability and lineage required.
A. Only statement 1 is correct
B. Only statement 3 is correct
C. Both statements 1 and 2 are correct
D.
Both statements 2 and 3 are correct
A. It is used to access source data.
B. It links data from different sources.
C. It provides data to BI server.
A. It is used to remove data from data warehouse (DWH).
B. It is used to modify DWH data.
C. It involves the process of data collection in different forms and making them uniformly consistent with each other.
D. t is a process of loading transformed data into the data warehouse.
Which of the following are the components of a logical data warehouse?
1. Repository Management
2. Auditing Statistics and Performance Evaluation Services
3. SLA Management
A. All 1, 2, 3
B. Only 1 and 2
C. Only 2 and 3
D. Only 1 and 3
A. Data virtualization can augment the capabilities of a data warehouse.
B. Self-service Bl methods can be facilitated through data virtualization.
C. Data virtualization cannot help in prototyping and sandboxing.
D. All of the above statements are correct.
A.
No communication between clients and services can take place ifthe ESB is down.
B.
It can decrease the performance of client-service communication due to extra level of indirection.
C.
It cannot authenticate and authorize a client before forwarding service requests to services.
A. Data abstraction is the handling Of data in meaningful ways.
B. Abstract properties are visible to the consumer of abstracted data type.
C. Physical instances are visible to the consumer of abstracted data type.
D. Abstraction allows data consumers to leverage the adoption of XML industry standards.
Which of the following are the technical benefits that are Obtained through data virtualization over data materialization?
1. Ease Of data integration
2. Iterative development
3. Increased developer productivity
A. All 1, 2, 3
B. Only 1, 2
C. Only 1, 3
D. Only 2, 3
Which of the following statements are correct about decision support system (D85) and business intelligence (8|)?
1. Decision support system is a computer program application that can be used to analyze business data.
2. Business intelligence (Bl) can be used to present business data, whereas decision support system (DSS) cannot be used.
3. Business intelligence is a category of applications and technologies that can be used for collecting, storing and analyzing data.
A. All 1, 2, 3 are correct
B. Only 1, 2 are correct
C. Only 2, 3 are correct
D. Only 1, 3 are correct
A. File-based data access
B. Object-based storage
C. Block-based data access
D. None of the above
A. Component schema
B. External schema
C. Export schema
D. Federated schema
A. 3 Sharing of meta data specification
B. 3 Decoupling of data consumers and data stores
C. 3 Both a and b
D. 2) Neither a nor b
In which of the following techniques, data is copied from the source either record-wise or transaction-Wise?
A. Exact transfer load
B. Replication
C. Exact Load transform
D. Both b and c
A. Data source layer
B. Application layer
C. Physical layer
D. None of the above
A. Business layer
B. Physical layer
C. Application layer
D. Both b and c
A. Schema on read.
B. Schema on write.
C. Both a and b are used in the traditional Bl architecture.
D. None of the above is used in the traditional Bl architecture.
A. It provides low data consistency.
B. It provides support for consolidated analytics platform.
C. Performing custom analytics on data warehouse brings down the performance of the DWI-l
D. Both b and c are correct.
A. Production databases
B. Replicated databases
C. Both a and b
A. Data flow within an organization and business to business transactions cannot be visualized.
B. Relationships between process flows cannot be visualized.
C. It can limit innovations
D. None of the above.
A. Application layer
B. Physical layer
C. Data sources layer
D. Consumer layer
A. Physical layer
B. Application layer
C. Business layer
D. All of the above
A. Denormalized schemas
B. Normalized schemas
C. Either of the above given options
Which of the following options are the existing components of a traditional Bl big data framework?
1. DWH
2. OLAP
3. Metadata
4. Reports
A. Only 1, 3, 4
B. Only 1, 2, 3
C. Only 1, 2, 4
D. All 1, 2, 3, 4
A. Yes
B. No
A. Model-driven DSS
B. Document-driven DSS
C. Communication-driven and group DSS
D. None of the above
A. It imposes a heterogeneous data model.
B. It cannot impact the response time of an operational system.
C. It decreases the requirement of data storage.
D. None of the above statements is correct
A. Data warehouse
B. Online analytical processing (OLAP)
C. Business performance management (BPM)
D. a and c
E. a. b and c
A virtual data warehouse can be developed by using which Of the following options?
1. Data marts
2. Production databases
3. Data virtualization server
A.
All 1. 2 and 3 can be used
B.
Only1 and 3 can be used
C.
Only 1 and 2 can be used
D.
A.
All 1. 2 and 3 can be performed.
B.
Only1 and 3 can be performed.
C.
Only 2 and 3 can be performed.
D.
With reference to data integration problem, which of the following serve an example of uniform data access that are personalized doorways to intranet or internet. and where every user is provided with information according to their requirement?
A.
Data Warehouses
B. Portals
C. Operational data stores
D.
A. Star schema
B. Snowflake schema
C. Both star schema and snowflake schema
D. Neither star schema nor snowflake schema
Which of the following statements is NOT correct about snowflake schemas in business intelligence architecture?
A.
Tables are organized around a central fact table.
B.
Surrogate keys are not used.
C.
A fact table has relationships only with the dimension tables.
With reference to federated database systems (FDBSs), which of the following schemas is used to
represent a subset of a component schema that is available to a specific federation?
A.
B.
C.
A. Accounting and financial models
B. Representational models
C. Optimization models
D. None of the above
A. Operational data store
B. Data staging area
C. Data warehouse
D. Data mart
A. They are instances of applications.
B. They can be created from physical databases as well as abstracted databases.
C. They cannot be created from APls.
D. They cannot be created quickly.
A. Only the functionality of the component systems is responsible
B. Lack of storage capacity
C. The architectural view of an information system
D. Only the business rules and integrity constraints are responsible
A. Production data stores
B. Data staging areas
C. Data marts
D. None of the above
A. PDSs
B. Data staging areas
C. Data marts
D. Production data stores
A. Virtual tables
B. Source tables
C. Mappings
D. SOAP services
A. Denodo Technologies
B. IBM
C. lnformatica
D. None of the above
A. Defining mappings
B. Defining data structures
C. Defining ETL logic for data transformation
D. Enabling caching
A. Designing data structures
B. Defining mappings
C. Defining virtual tables
D. Installing a database server
A. It reduces the cost.
B. It supports simple and powerful interfaces for querying data using JSON that enables quick development of applications.
C. It provides support for semi-structured data.
D. It does not provide support for unstructured data.
A. Production database
B. Data warehouse (DWH)
C. Personal data store (PDS)
D. Both a and b
E. Both b and c
A. Data warehouse focuses on Data in. whereas operational database focuses on Information out
B. Data warehouse contains historical data, whereas operational database contains current data
C. Data warehouse provides consolidated data. whereas operational database provides highly detailed data.
D. Data warehouse is used to analyze business. whereas operational database is used to run the Business.
A. It reduces the risk of data errors.
B. It increases the speed to access data.
C. It does not require a governance approach to avoid budgeting issues.
D. It is suitable for recording historic data snapshots.
A. Data owners lose control over their data that leads to security and privacy issues.
B. It has short initial implementation time but cost is high
C. It takes time and costs high to add new data sources.
D. It provides unlimited flexibility of use and types of users.
A. It is a business intelligence architecture.
B. It delivers data to data consumers but does not deliver meta data.
C. It can deliver data that is stored in production systems/warehouses but cannot deliver from data mart
D. It can deliver unstructured data to data consumers.
A. It cannot be used in place of a data warehouse.
B. it can be used for an organization whose data is stored off-site by a third party cloud service provider.
C. it can be used as an enhancement to add attributes, which are not supported by data warehouse API.
D. All the statements given above are correct.
A. Operational data store
B. Production database
C. Personal data store
D. Data staging area
A. Cost/Budget is limited
B. Time urgency for solution implementation
C. Small data query result sets required
D. Data source is multidimensional
A. Email
B. GIS
C. EIS
D. Video conference
A. Data abstraction is used to hide complexity.
B. Data abstraction is used to simplify information access.
C. It provides separate business views of data to every consumer.
D. It provides end-to-end control.
A. Data warehouse (DWH) data can be exposed to business users in the form of analytics and user-friendly reports through Bl tools.
B. OLAP cubes and metadata can be used to provide ad-hoc analysis capabilities to the end users.
C. Analytics tools cannot be run on a warehouse to discover patterns.
D. Analytics tools can be run on a warehouse to generate trends and forecasts .
A. Data types
B. Ranges
C. Indexes
D. Queries
A. True
B. XEN
C. False
D. None of the above
A. Default VLAN
B. BPDU filter
C. Virtual server
D. VLAN hopping attack
A. Windowstate
B. Fixeddouble
C. Minmaxsize
D. FormBorderStyle